Estructura y tipología de los Aenigmata Symphosii.

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Towards End-to-End Acoustic Localization using Deep Learning: from Audio Signal to Source Position Coordinates

This paper presents a novel approach for indoor acoustic source localization using microphone arrays and based on a Convolutional Neural Network (CNN). The proposed solution is, to the best of our knowledge, the first published work in which the CNN is designed to directly estimate the three dimensional position of an acoustic source, using the raw audio signal as the input information avoiding the use of hand crafted audio features. Given the limited amount of available localization data, we propose in this paper a training strategy based on two steps. We first train our network using semi-synthetic data, generated from close talk speech recordings, and where we simulate the time delays and distortion suffered in the signal that propagates from the source to the array of microphones. We then fine tune this network using a small amount of real data. Our experimental results show that this strategy is able to produce networks that significantly improve existing localization methods based on \textit{SRP-PHAT} strategies. In addition, our experiments show that our CNN method exhibits better resistance against varying gender of the speaker and different window sizes compared with the other methods.Comment: 18 pages, 3 figures, 8 table

Notas críticas del humanista Iosephus Castalio a los Aenigmata Symphosii.

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Tractatus de conceptu. Tractatus de sterilitate mulierum, edición crítica, traducción, introducciones y notas de Pedro Conde Panado, Enrique Montero Cartelle y María Cruz Herrero Ingelmo.

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CICERÓN, Pro Archia Poeta oratio, Introducción, traducción y notas de Antonio Espigares Pinilla.

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Krylov methods for large-scale modern problems in numerical linear algebra

Large-scale problems have attracted much attention in the last decades since they arise from different applications in several fields. Moreover, the matrices that are involved in those problems are often sparse, this is, the majority of their entries are zero. Around 40 years ago, the most common problems related to large-scale and sparse matrices consisted in solving linear systems, finding eigenvalues and/or eigenvectors, solving least square problems or computing singular value decompositions. However, in the last years, large-scale and sparse problems of different natures have appeared, motivating and challenging numerical linear algebra to develop effective and efficient algorithms to solve them. Common difficulties that appear during the development of algorithms for solving modern large-scale problems are related to computational costs, storage issues and CPU time, given the large size of the matrices, which indicate that direct methods can not be used. This suggests that projection methods based on Krylov subspaces are a good option to develop procedures for solving large-scale and sparse modern problems. In this PhD Thesis we develop novel and original algorithms for solving two large-scale modern problems in numerical linear algebra: first, we introduce the R-CORK method for solving rational eigenvalue problems and, second, we present projection methods to compute the solution of T-Sylvester matrix equations, both based on Krylov subspaces. The R-CORK method is an extension of the compact rational Krylov method (CORK) [104] introduced to solve a family of nonlinear eigenvalue problems that can be expressed and linearized in certain particular ways and which include arbitrary polynomial eigenvalue problems, but not arbitrary rational eigenvalue problems. The R-CORK method exploits the structure of the linearized problem by representing the Krylov vectors in a compact form in order to reduce the cost of storage, resulting in a method with two levels of orthogonalization. The first level of orthogonalization works with vectors of the same size as the original problem, and the second level works with vectors of size much smaller than the original problem. Since vectors of the size of the linearization are never stored or orthogonalized, R-CORK is more efficient from the point of view of memory and orthogonalization costs than the classical rational Krylov method applied to the linearization. Moreover, since the R-CORK method is based on a classical rational Krylov method, the implementation of implicit restarting is possible and we present an efficient way to do it, that preserves the compact representation of the Krylov vectors. We also introduce in this dissertation projection methods for solving the TSylvester equation, which has recently attracted considerable attention as a consequence of its close relation to palindromic eigenvalue problems and other applications. The theory concerning T-Sylvester equations is rather well understood, and before the work in this thesis, there were stable and efficient numerical algorithms to solve these matrix equations for small- to medium- sized matrices. However, developing numerical algorithms for solving large-scale T-Sylvester equations was a completely open problem. In this thesis, we introduce several projection methods based on block Krylov subspaces and extended block Krylov subspaces for solving the T-Sylvester equation when the right-hand side is a low-rank matrix. We also offer an intuition on the expected convergence of the algorithm based on block Krylov subspaces and a clear guidance on which algorithm is the most convenient to use in each situation. All the algorithms presented in this thesis have been extensively tested, and the reported numerical results show that they perform satisfactorily in practice.Adicionalmente se recibió ayuda parcial de los proyectos de investigación: “Structured Numerical Linear Algebra: Matrix Polynomials, Special Matrices, and Conditioning” (Ministerio de Economía y Competitividad de España, Número de proyecto: MTM2012-32542) y “Structured Numerical Linear Algebra for Constant, Polynomial and Rational Matrices” (Ministerio de Economía y Competitividad de España, Número de proyecto: MTM2015-65798-P), donde el investigador principal de ambos proyectos fue Froilán Martínez Dopico.Programa Oficial de Doctorado en Ingeniería MatemáticaPresidente: José Mas Marí.- Secretario: Fernando de Terán Vergara.- Vocal: José Enrique Román Molt

Degradation and Vulnerability to Climate Change in High Andean Rangelands

Rangeland degradation is a process associated with loss of ecosystem equilibrium. Therefore, this work seeks to identify the most important factors that cause the degradation process of rangelands, assess the degree of degradation and vulnerability to current climate change of these ecosystems; and determine if there is a relationship between the degree of rangeland degradation and vulnerability to climate change in high Andean rangelands. The study was located in the central highlands of Peru (Ancash, Junín, Pasco, Huancavelica and Lima) and involved the design of a framework to assess rangeland degradation based on field information and Landsat satellite products that was contrasted with socioeconomic, ecological and location variables. The estimation of vulnerability to climate change was assessed with the Analytic hierarchy process (AHP) in a Geographic Information Systems (GIS) platform. The results revealed that around 80% of the rangelands were classified as extreme and serious degraded. Extreme and heavy vulnerability was around 85%. There is positive spatial correlation between degradation and vulnerability to climate change in high Andean rangelands (Pearson = 0.67, Spearman = 0.61)

Notas sobre urbanismo y mentalidad urbana en Trujillo de los siglos XVI al XIX

El objetivo del presente estudio es doble; en primer lugar, pretende ser una aproximación a la historia urbana de Trujillo en los siglos XVIII y XIX, apoyándose para esto en dos fuentes fundamentales para cualquier estudio de estas características: El Catastro de Ensenada (1753) y el plano de Coello (alrededor de 1850). Los datos proporcionados por Madoz, las Visitas de la Real Audiencia de Extremadura y aquéllos obtenidos de los acuerdos municipales de Trujillo, completaron documentalmente el trabajo de investigación. En segundo lugar, y dado que la estructura urbana de la época antes determinada es, lógicamente, heredera de tiempos pasados, tratamos de bosquejar la evolución de los elementos urbanos que, fundamentalmente, desde el siglo XVI determinan la estructura planimétrica y arquitectónica de la ciudad en los siglos XVIII y XIX. Los sucesivos cambios apreciados en el desarrollo histórico de la mentalidad urbanística, inspiradora en gran medida de una determinada actuación sobre lo urbano, pueden explicar los resultados derivados de la segunda meta propuesta y constituir la hipótesis fundamental del trabajo

Abandono y ruina de la arquitectura trujillana durante el siglo XIX

El siglo XIX constituye una época en que lo urbano va a caracterizarse por la continua búsqueda de soluciones a los problemas que se plantean en relación a nuevas y apremiantes necesidades. El desarrollo demográfico exige un incremento del número de viviendas, un desarrollo urbano que dará a las ciudades una nueva dimensión. Es el siglo de los grandes planes de ensanche urbano, pero es también la época de la desaparición de buena parte del legado histórico-artístico de nuestra arquitectura, que muchas veces será sacrificado en aras de un, no siempre acertado, «urbanismo de sustitución». Desde principios del siglo XVII a los comienzos del XIX, transcurren para la historia urbana de Trujillo dos centurias de muy reducida actividad constructiva tanto en el orden de la arquitectura civil como en el de la religiosa. Este letargo va a ir acompañado de un paulatino proceso de ruina que llega en el siglo XIX a su máxima expresión y que, en virtud de las necesidades y de las posibilidades del municipio o de la comunidad religiosa, no gozará de un tratamiento uniforme