Research methods and didactic to carry out an essay about history of schooling

El alumnado de primer curso del Doble Grado en Educación Primaria y Estudios ingleses, de nueva implantación en la Universidad de Málaga, accede a la asignatura de Historia de la Escuela sin el más mínimo conocimiento de la cuestión, es decir, partiendo de cero, y sin las herramientas crítico-analíticas básicas para aprobar la asignatura, dada su procedencia de un sistema basado en la memorización acrítica. Este material docente universitario pretende ayudar a que aprueben la asignatura

Stochastic Discriminative EM

Stochastic discriminative EM (sdEM) is an online-EM-type algorithm for discriminative training of probabilistic generative models belonging to the exponential family. In this work, we introduce and justify this algorithm as a stochastic natural gradient descent method, i.e. a method which accounts for the information geometry in the parameter space of the statistical model. We show how this learning algorithm can be used to train probabilistic generative models by minimizing different discriminative loss functions, such as the negative conditional log-likelihood and the Hinge loss. The resulting models trained by sdEM are always generative (i.e. they define a joint probability distribution) and, in consequence, allows to deal with missing data and latent variables in a principled way either when being learned or when making predictions. The performance of this method is illustrated by several text classification problems for which a multinomial naive Bayes and a latent Dirichlet allocation based classifier are learned using different discriminative loss functions.Comment: UAI 2014 paper + Supplementary Material. In Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence (UAI 2014), edited by Nevin L. Zhang and Jian Tian. AUAI Pres

Probabilistic Graphical Models on Multi-Core CPUs using Java 8

In this paper, we discuss software design issues related to the development of parallel computational intelligence algorithms on multi-core CPUs, using the new Java 8 functional programming features. In particular, we focus on probabilistic graphical models (PGMs) and present the parallelisation of a collection of algorithms that deal with inference and learning of PGMs from data. Namely, maximum likelihood estimation, importance sampling, and greedy search for solving combinatorial optimisation problems. Through these concrete examples, we tackle the problem of defining efficient data structures for PGMs and parallel processing of same-size batches of data sets using Java 8 features. We also provide straightforward techniques to code parallel algorithms that seamlessly exploit multi-core processors. The experimental analysis, carried out using our open source AMIDST (Analysis of MassIve Data STreams) Java toolbox, shows the merits of the proposed solutions.Comment: Pre-print version of the paper presented in the special issue on Computational Intelligence Software at IEEE Computational Intelligence Magazine journa

Analytical Models of the Performance of C-V2X Mode 4 Vehicular Communications

The C-V2X or LTE-V standard has been designed to support V2X (Vehicle to Everything) communications. The standard is an evolution of LTE, and it has been published by the 3GPP in Release 14. This new standard introduces the C-V2X or LTE-V Mode 4 that is specifically designed for V2V communications using the PC5 sidelink interface without any cellular infrastructure support. In Mode 4, vehicles autonomously select and manage their radio resources. Mode 4 is highly relevant since V2V safety applications cannot depend on the availability of infrastructure-based cellular coverage. This paper presents the first analytical models of the communication performance of C-V2X or LTE-V Mode 4. In particular, the paper presents analytical models for the average PDR (Packet Delivery Ratio) as a function of the distance between transmitter and receiver, and for the four different types of transmission errors that can be encountered in C-V2X Mode 4. The models are validated for a wide range of transmission parameters and traffic densities. To this aim, this study compares the results obtained with the analytical models to those obtained with a C-V2X Mode 4 simulator implemented over Veins

X-ray spectral variability of LINERs selected from the Palomar sample

Variability is a general property of active galactic nuclei (AGN). At X-rays, the way in which these changes occur is not yet clear. In the particular case of low ionisation nuclear emission line region (LINER) nuclei, variations on months/years timescales have been found for some objects, but the main driver of these changes is still an open question. The main purpose of this work is to investigate the X-ray variability in LINERs, including the main driver of such variations, and to search for eventual differences between type 1 and 2 objects. We use the 18 LINERs in the Palomar sample with data retrieved from Chandra and/or XMM-Newton archives corresponding to observations gathered at different epochs. All the spectra for the same object are simultaneously fitted in order to study long term variations. The nature of the variability patterns are studied allowing different parameters to vary during the spectral fit. Whenever possible, short term variations from the analysis of the light curves and UV variability are studied.Comment: 49 pages, accepted. arXiv admin note: text overlap with arXiv:1305.222

La Praefatio de la traducción latina del Corán de Germán de Silesia

Como anticipo de la edición crítica de la traducción al latín del Corán, realizada por Domingo Germán de Silesia, se presentan algunos datos importantes sobre el autor y la obra, con un comentario a la misma, que contiene interesantes datos sobre los motivos que indujeron a su composición, así como su intención y estilo. Termina el trabajo con la edición de la mencionada Praefatio.As an advance to his forthcoming critical edition of the Latin translation of the Koran by Germain of Silesia, the author presents relevant data both on the translator and on his work. Besides, he includes an analysis of the translation's Praefatio, which provides interesting information on the reasons of the translation, as well as on its purpose and style. The paper concludes with the edition of the Praefatio itself