Link prediction using a probabilistic description logic

Due to the growing interest in social networks, link prediction has received significant attention. Link prediction is mostly based on graph-based features, with some recent approaches focusing on domain semantics. We propose algorithms for link prediction that use a probabilistic ontology to enhance the analysis of the domain and the unavoidable uncertainty in the task (the ontology is specified in the probabilistic description logic crALC). The scalability of the approach is investigated, through a combination of semantic assumptions and graph-based features. We evaluate empirically our proposal, and compare it with standard solutions in the literature.

Finite element methods for the Stokes system based on a Zienkiewicz type N-simplex

Hermite interpolation is increasingly showing to be a powerful numerical solution tool, as applied to different kinds of second order boundary value problems. In this work we present two Hermite finite element methods to solve viscous incompressible flows problems, in both two- and three-dimension space. In the two-dimensional case we use the Zienkiewicz triangle to represent the velocity field, and in the three-dimensional case an extension of this element to tetrahedra, still called a Zienkiewicz element. Taking as a model the Stokes system, the pressure is approximated with continuous functions, either piecewise linear or piecewise quadratic, according to the version of the Zienkiewicz element in use, that is, with either incomplete or complete cubics. The methods employ both the standard Galerkin or the Petrov–Galerkin formulation first proposed in Hughes et al. (1986) [18], based on the addition of a balance of force term. A priori error analyses point to optimal convergence rates for the PG approach, and for the Galerkin formulation too, at least in some particular cases. From the point of view of both accuracy and the global number of degrees of freedom, the new methods are shown to have a favorable cost-benefit ratio, as compared to velocity Lagrange finite elements of the same order, especially if the Galerkin approach is employed.

Formalizing languages for service oriented computing

Service Oriented Computing is a new programming paradigm for addressing distributed system design issues. Services are autonomous computational entities which can be dynamically discovered and composed in order to form more complex systems able to achieve different kinds of task. E-government, e-business and e-science are some examples of the IT areas where Service Oriented Computing will be exploited in the next years. At present, the most credited Service Oriented Computing technology is that of Web Services, whose specifications are enriched day by day by industrial consortia without following a precise and rigorous approach. This PhD thesis aims, on the one hand, at modelling Service Oriented Computing in a formal way in order to precisely define the main concepts it is based upon and, on the other hand, at defining a new approach, called bipolar approach, for addressing system design issues by synergically exploiting choreography and orchestration languages related by means of a mathematical relation called conformance. Choreography allows us to describe systems of services from a global view point whereas orchestration supplies a means for addressing such an issue from a local perspective. In this work we present SOCK, a process algebra based language inspired by the Web Service orchestration language WS-BPEL which catches the essentials of Service Oriented Computing. From the definition of SOCK we will able to define a general model for dealing with Service Oriented Computing where services and systems of services are related to the design of finite state automata and process algebra concurrent systems, respectively. Furthermore, we introduce a formal language for dealing with choreography. Such a language is equipped with a formal semantics and it forms, together with a subset of the SOCK calculus, the bipolar framework. Finally, we present JOLIE which is a Java implentation of a subset of the SOCK calculus and it is part of the bipolar framework we intend to promote.

Probabilistic Envelope Curves for Extreme Rainfall Events - Curve Inviluppo Probabilistiche per Precipitazioni Estreme

A regional envelope curve (REC) of flood flows summarises the current bound on our experience of extreme floods in a region. RECs are available for most regions of the world. Recent scientific papers introduced a probabilistic interpretation of these curves and formulated an empirical estimator of the recurrence interval T associated with a REC, which, in principle, enables us to use RECs for design purposes in ungauged basins. The main aim of this work is twofold. First, it extends the REC concept to extreme rainstorm events by introducing the Depth-Duration Envelope Curves (DDEC), which are defined as the regional upper bound on all the record rainfall depths at present for various rainfall duration. Second, it adapts the probabilistic interpretation proposed for RECs to DDECs and it assesses the suitability of these curves for estimating the T-year rainfall event associated with a given duration and large T values. Probabilistic DDECs are complementary to regional frequency analysis of rainstorms and their utilization in combination with a suitable rainfall-runoff model can provide useful indications on the magnitude of extreme floods for gauged and ungauged basins. The study focuses on two different national datasets, the peak over threshold (POT) series of rainfall depths with duration 30 min., 1, 3, 9 and 24 hrs. obtained for 700 Austrian raingauges and the Annual Maximum Series (AMS) of rainfall depths with duration spanning from 5 min. to 24 hrs. collected at 220 raingauges located in northern-central Italy. The estimation of the recurrence interval of DDEC requires the quantification of the equivalent number of independent data which, in turn, is a function of the cross-correlation among sequences. While the quantification and modelling of intersite dependence is a straightforward task for AMS series, it may be cumbersome for POT series. This paper proposes a possible approach to address this problem.

Probabilistic approaches in civil engineering: generation of random fields and structural identification with genetic algorithms

The inherent stochastic character of most of the physical quantities involved in engineering models has led to an always increasing interest for probabilistic analysis. Many approaches to stochastic analysis have been proposed. However, it is widely acknowledged that the only universal method available to solve accurately any kind of stochastic mechanics problem is Monte Carlo Simulation. One of the key parts in the implementation of this technique is the accurate and efficient generation of samples of the random processes and fields involved in the problem at hand. In the present thesis an original method for the simulation of homogeneous, multi-dimensional, multi-variate, non-Gaussian random fields is proposed. The algorithm has proved to be very accurate in matching both the target spectrum and the marginal probability. The computational efficiency and robustness are very good too, even when dealing with strongly non-Gaussian distributions. What is more, the resulting samples posses all the relevant, welldefined and desired properties of “translation fields”, including crossing rates and distributions of extremes. The topic of the second part of the thesis lies in the field of non-destructive parametric structural identification. Its objective is to evaluate the mechanical characteristics of constituent bars in existing truss structures, using static loads and strain measurements. In the cases of missing data and of damages that interest only a small portion of the bar, Genetic Algorithm have proved to be an effective tool to solve the problem.

3-D Boundary element-finite element method for the dynamic analysis of piled buildings.

[EN]A boundary element-finite element model is presented for the three-dimensional dynamic analysis of piled buildings in the frequency domain. Piles are modelled as compressible Euler-Bernoulli beams founded on a linear, isotropic, viscoelastic, zoned-homogeneous, unbounded layered soil, while multi-storey buildings are assumed to be comprised of vertical compressible piers and rigid slabs.

Finite element simulation of a local scale air quality model over complex terrain

[EN]In this paper we propose a finite element method approach for modelling the air quality in a local scale over complex terrain. The area of interest is up to tens of kilometres and it includes pollutant sources. The proposed methodology involves the generation of an adaptive tetrahedral mesh, the computation of an ambient wind field, the inclusion of the plume rise effect in the wind field, and the simulation of transport and reaction of pollutants. We apply our methodology to simulate a fictitious pollution episode in La Palma island (Canary Island, Spain)...

Adaptive finite element simulation of stack pollutant emissions over complex terrains

[EN]A three-dimensional finite element model for the pollutant dispersion is presented. In these environmental processes over a complex terrain, a mesh generator capable of adapting itself to the topographic characteristics is essential. The first stage of the model consists on the construction of an adaptive tetrahedral mesh of a rectangular region bounded in its lower part by the terrain and in its upper part by a horizontal plane. Once the mesh is constructed, an adaptive local refinement of tetrahedra is used in order to capture the plume rise. Wind measurements are used to compute an interpolated wind field, that is modified by using a mass-consistent model and perturbing its vertical component to introduce the plume rise effect...

Three-dimensional finite element modelling of stack pollutant emissions

[EN]In this paper we propose a finite element method approach for modelling the air quality in a local scale over complex terrain. The area of interest is up to tens of kilometres and it includes pollutant sources. The proposed methodology involves the generation of an adaptive tetrahedral mesh, the computation of an ambient wind field, the inclusion of the plume rise effect in the wind field, and the simulation of transport and reaction of pollutants. The methodology is used to simulate a fictitious pollution episode in La Palma island (Canary Island, Spain)…

The meccano method for finite element and isogeometric analysis

Congresos y conferencias

Local scale finite element modelling of stack pollutant emissions

Congresos y conferencias

Calibration and validation of an air quality finite element model around an electric power plant in Gran Canaria island

[EN]This work presents the calibration and validation of an air quality finite element model applied to the surroundings of Jinamar electric power plant in Gran Canaria island (Spain). The model involves the generation of an adaptive tetrahedral mesh, the computation of an ambient wind field, the inclusion of the plume rise effect in the wind field, and the simulation of transport and reaction of pollutants. The main advantage of the model is the treatment of complex terrains that introduces an alternative to the standard implementation of current models. In addition, it improves the computational cost through the use of unstructured meshes...

Adaptive Finite Element Method with a local element parametrization nested meses

[EN]This work presents a novel approach to solve a two dimensional problem by using an adaptive finite element approach. The most common strategy to deal with nested adaptivity is to generate a mesh that represents the geometry and the input parameters correctly, and to refine this mesh locally to obtain the most accurate solution. As opposed to this approach, the authors propose a technique using independent meshes : geometry, input data and the unknowns. Each particular mesh is obtained by a local nested refinement of the same coarse mesh at the parametric space…