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Formica A.,CNR Institute for System Analysis and Computer Science Antonio Ruberti
International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems | Year: 2010

This paper presents a method for evaluating concept similarity within Fuzzy Formal Concept Analysis. In the perspective of developing the Semantic Web, such a method can be helpful when the digital resources found on the Internet cannot be treated equally and the integration of fuzzy data becomes fundamental for the search and discovery of information in the Web. © 2010 World Scientific Publishing Company. Source

Rendl F.,Klagenfurt University | Rinaldi G.,CNR Institute for System Analysis and Computer Science Antonio Ruberti | Wiegele A.,Klagenfurt University
Mathematical Programming | Year: 2010

We present a method for finding exact solutions of Max-Cut, the problem of finding a cut of maximum weight in a weighted graph.We use a Branch-and-Bound setting that applies a dynamic version of the bundle method as bounding procedure. This approach uses Lagrangian duality to obtain a "nearly optimal" solution of the basic semidefinite Max-Cut relaxation, strengthened by triangle inequalities. The expensive part of our bounding procedure is solving the basic semidefinite relaxation of the Max-Cut problem, which has to be done several times during the bounding process. We review other solution approaches and compare the numerical results with our method. We also extend our experiments to instances of unconstrained quadratic 0-1 optimization and to instances of the graph equipartition problem. The experiments show that our method nearly always outperforms all other approaches. In particular, for dense graphs, where linear programming-based methods fail, our method performs very well. Exact solutions are obtained in a reasonable time for any instance of size up to n = 100, independent of the density. For some problems of special structure we can solve even larger problem classes. We could prove optimality for several problems of the literature where, to the best of our knowledge, no other method is able to do so. © Springer-Verlag 2008. Source

Carravetta F.,CNR Institute for System Analysis and Computer Science Antonio Ruberti
IEEE Transactions on Automatic Control | Year: 2011

A 2-D-stochastic realization is obtained for an homogeneous discrete Gaussian Markov-field in two dimensions. In specific, it is shown that such Markov fields can be represented as the (unique) pathwise solution of a 2-D-recursive system of equations, with a locally-correlated forcing-noise. The idea of stochastic dynamic system in two dimensions gets realized this way. Two types of domain are considered: spheric and rectangular. © 2011 IEEE. Source

D'Onofrio A.,Italian National Cancer Institute | Gandolfi A.,CNR Institute for System Analysis and Computer Science Antonio Ruberti
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2010

Tumor angiogenesis is a landmark of solid tumor development, but it is also directly relevant to chemotherapy. Indeed, the density and quality of neovessels may influence the effectiveness of therapies based on blood-born agents. In this paper, first we define a deterministic model of antiproliferative chemotherapy in which the drug efficacy is a unimodal function of vessel density, and then we show that under constant continuous infusion therapy the tumor-vessel system may be multistable. However, the actual drug concentration profiles are affected by bounded even if possibly large fluctuations. Through numerical simulations, we show that the tumor volume may undergo transitions to the higher equilibrium value induced by the bounded noise. In case of periodically delivered boli-based chemotherapy, we model the fluctuations due to time variability of both the drug clearance rate and the distribution volume, as well as those due to irregularities in drug delivery. We observed noise-induced transitions also in case of periodic delivering. By applying a time dense scheduling with constant average delivered drug (metronomic scheduling), we observed an easier suppression of the transitions. Finally, we propose to interpret the above phenomena as an unexpected non-genetic kind of resistance to chemotherapy. © 2010 The American Physical Society. Source

White L.B.,University of Adelaide | Carravetta F.,CNR Institute for System Analysis and Computer Science Antonio Ruberti
IEEE Transactions on Automatic Control | Year: 2011

This technical note addresses modelling and estimation of a class of finite state random processes called hidden reciprocal chains (HRC). A hidden reciprocal chain consists of a finite state reciprocal process, together with an observation process conditioned on the reciprocal process much as in the case of a hidden Markov model (HMM). The key difference between Markov models and reciprocal models is that reciprocal models are non-causal. The technical note presents a characterization of a HRC by a finite set of hidden Markov bridges, which are HMMs with the final state fixed. The technical note then uses this characterization to derive the optimal fixed interval smoother for a HRC. Performance of linear and optimal smoothers derived for both HMM and HRC are compared (using simulations) for a class of HRC derived from underlying Markov transitions. These experiments suggest that, not surprisingly, the performance of the optimal HMM and HRC smoothers are signifcantly better than their linear counterparts, and that some performance improvement is obtained using the HRC smoothers compared to the HMM smoothers. The technical note concludes by mentioning some ongoing and future work which exploits this new Markov bridge characterization of a HRC. © 2011 IEEE. Source

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