Trabajos migrados en revisión - FAMAF - Partes de libro 2015Memoria Sigeva 2015http://hdl.handle.net/11086/144332024-03-29T01:13:59Z2024-03-29T01:13:59ZModal satisfiability via SMT solvingAreces, Carlos EduardoFontaine, PascalMerz, Stephanhttp://hdl.handle.net/11086/221122023-12-13T18:13:46Z2015-01-01T00:00:00ZModal satisfiability via SMT solving
Areces, Carlos Eduardo; Fontaine, Pascal; Merz, Stephan
Modal logics extend classical propositional logic, and they are robustly decidable. Whereas most existing decision procedures for modal logics are based on tableau constructions, we propose a framework for obtaining decision procedures by adding instantiation rules to standard SAT and SMT solvers. Soundness, completeness, and termination of the procedures can be proved in a uniform and elementary way for the basic modal logic and some extensions.
2015-01-01T00:00:00ZAplicación del método científico como función de la escala del sistemaMoreschi, Osvaldo M.http://hdl.handle.net/11086/219952022-10-13T11:41:51Z2015-01-01T00:00:00ZAplicación del método científico como función de la escala del sistema
Moreschi, Osvaldo M.
Presentamos un estudio de la modalidad en que se aplica el método científico en diversas investigaciones, como función de la escala del sistema bajo estudio, concentrándonos principalmente en los aspectos físicos de las ciencias naturales, basándonos en un conjunto de ejemplos seleccionados. Primeramente debemos realizar una breve descripción de lo que entenderemos por método científico; lo cual no sería nuestro tema, sino su utilización. Brevemente señalaremos distintos tipos de conocimiento que se obtienen en ciencias naturales. Presentamos varios ejemplos de cómo se emplea el método científico para sistemas con escalas cada vez más grandes. Realizamos una descripción cualitativa de dicho comportamiento.
2015-01-01T00:00:00ZConsidering correlation properties on statistical simulation of clutterFlesia, Ana GeorginaLucini, María MagdalenaPérez, Darío Javierhttp://hdl.handle.net/11086/219812023-12-13T18:14:42Z2015-01-01T00:00:00ZConsidering correlation properties on statistical simulation of clutter
Flesia, Ana Georgina; Lucini, María Magdalena; Pérez, Darío Javier
Statistical properties of image data are of paramount importance in the design of pattern recognition technics and the interpretation of their outputs. Image simulation allows quantification of method?s error and accuracy. In the case of SAR images, the contamination they suffer from a particular kind of noise, called speckle, which does not follow the classical hypothesis of entering the signal in an additive manner and obeying the Gaussian law, make them require a more careful treatment. Since the seminal work of Frery et al. (1997) a great variety of studies have been made targeting the specification of statistical properties of SAR data beyond classical assumptions. The G distribution family proposed by Frery has been proved a flexible tool for the design of pattern recognition algorithms based on statistical modeling. Nevertheless, most of such work does not consider correlation present in the data as significant, which introduces an error in the model of particular regions of the imagery. The autocorrelation function can represent the structure of sea waves and the random variation made by the height and width of trees, along with the variability introduced in forests by the variation of wind intensity. Using the roughness parameter of the G family for target discrimination alleviates this modeling error, since it was shown by Frery et al. (1997) that it characterizes heterogeneity in data. Classification accuracy is then tied to parameter estimation, which in this case it has been proved difficult, Lucini (2002), Bustos et al. (2002). In this paper we review some of our own simulation techniques to generate SAR clutter with pre-specified correlation properties, Flesia (1999), Bustos et al. (2001), Bustos et al. (2009), and release a new set of routines in R for simulation studies based on such techniques. We give an example of the code versatility studying the change in accuracy of non-parametric techniques when correlated data is classified, compared with classification of uncorrelated data simulated with the same parameters. All code is available for download from AGF?s Reproducible Research website, Flesia (2014).
2015-01-01T00:00:00ZZoom : a corpus of natural language descriptions of map locationsAltamirano, Ivana RominaFerreira, ThiagoParaboni, IvandréBenotti, Lucianahttp://hdl.handle.net/11086/219672022-10-13T11:41:49Z2015-01-01T00:00:00ZZoom : a corpus of natural language descriptions of map locations
Altamirano, Ivana Romina; Ferreira, Thiago; Paraboni, Ivandré; Benotti, Luciana
This paper describes an experiment to elicit referring expressions from human subjects for research in natural language generation and related fields, and preliminary results of a computational model for the generation of these expressions. Unlike existing resources of this kind, the resulting data set -the Zoom corpus of natural language descriptions of map locations- takes into account a domain that is significantly closer to real-world applications than what has been considered in previous work, and addresses more complex situations of reference, including contexts with different levels of detail, and instances of singular and plural reference produced by speakers of Spanish and Portuguese.
2015-01-01T00:00:00Z