Robust solutions to multi-objective linear programs with uncertain data

In this paper we examine multi-objective linear programming problems in the face of data uncertainty both in the objective function and the constraints. First, we derive a formula for the radius of robust feasibility guaranteeing constraint feasibility for all possible scenarios within a specified uncertainty set under affine data parametrization. We then present numerically tractable optimality conditions for minmax robust weakly efficient solutions, i.e., the weakly efficient solutions of the robust counterpart. We also consider highly robust weakly efficient solutions, i.e., robust feasible solutions which are weakly efficient for any possible instance of the objective matrix within a specified uncertainty set, providing lower bounds for the radius of highly robust efficiency guaranteeing the existence of this type of solutions under affine and rank-1 objective data uncertainty. Finally, we provide numerically tractable optimality conditions for highly robust weakly efficient solutions.

Fast pseudorandom generator based on packed matrices

Pseudorandom generators are a basic foundation of many cryptographic services and information security protocols. We propose a modification of a previously published matricial pseudorandom generator that significantly improves performance and security. The resulting generator is successfully compared to world class standards.

An optimized pseudorandom generator using packed matrices

Most cryptographic services and information security protocols require a dependable source of random data; pseudorandom generators are convenient and efficient for this application working as one of the basic foundation blocks on which to build the required security infrastructure. We propose a modification of a previously published matricial pseudorandom generator that significantly improves performance and security by using word packed matrices and modifying key scheduling and bit extraction schemes. The resulting generator is then successfully compared to world class standards.

Is video-case an efficient tool to complement the practical learning in real contexts? Effects on satisfaction and performance in Social Work Degree students

Este documento es un artículo inédito que ha sido aceptado para su publicación. Como un servicio a sus autores y lectores, Alternativas. Cuadernos de trabajo social proporciona online esta edición preliminar. El manuscrito puede sufrir alteraciones tras la edición y corrección de pruebas, antes de su publicación definitiva. Los posibles cambios no afectarán en ningún caso a la información contenida en esta hoja, ni a lo esencial del contenido del artículo.

Decodificando mediante microfósiles la Crisis de Salinidad del Mediterráneo como recurso didáctico en Ciencias de la Tierra

El estudio de las disciplinas científicas resulta más atractivo si se acompaña de actividades de carácter práctico. En este trabajo se propone un taller cuya finalidad es introducir al alumnado en el estudio de los microfósiles y de las reconstrucciones paleoambientales aplicándolo a uno de los eventos más significativos ocurridos en el área Mediterránea, que conllevó la desecación y posterior reinundación de toda la cuenca hace aproximadamente unos cinco millones de años. El taller consta de tres sesiones: una teórica, de introducción de los contenidos necesarios para el desarrollo de la actividad, una práctica, de obtención de datos, y una final, de interpretación de los cambios ambientales y presentación de los resultados en forma de artículo científico y posterior debate en el aula. Todos los datos necesarios para el desarrollo de la actividad se proporcionan en el presente artículo. Además, se proponen una serie de recursos bibliográficos y audiovisuales de fácil acceso para la introducción de los conceptos teóricos.

A multimodal genre recognition prototype

In this paper, a multimodal and interactive prototype to perform music genre classification is presented. The system is oriented to multi-part files in symbolic format but it can be adapted using a transcription system to transform audio content in music scores. This prototype uses different sources of information to give a possible answer to the user. It has been developed to allow a human expert to interact with the system to improve its results. In its current implementation, it offers a limited range of interaction and multimodality. Further development aimed at full interactivity and multimodal interactions is discussed.

Los microfósiles y la Crisis de Salinidad del Mediterráneo como recurso didáctico en Ciencias de la Tierra

El estudio de las disciplinas científicas resulta más atractivo si se acompaña de actividades de carácter práctico. En este trabajo se propone un taller cuya finalidad es introducir al alumnado en el trabajo científico que realizan los geólogos y paleontólogos a través de la información paleoambiental y bioestratigráfica que proporcionan los microfósiles y su aplicación a la Crisis de Salinidad del Messiniense. Este periodo es considerado como uno de los acontecimientos más relevantes de la historia geológica del Mediterráneo y se caracteriza por una acumulación masiva de evaporitas en el fondo de la cuenca, que se relaciona con la desecación y posterior reinundación del Mediterráneo hace aproximadamente cinco millones de años. El taller consta de tres sesiones: una teórica, de introducción de los contenidos necesarios para el desarrollo de la actividad, para la que se proponen una serie de recursos bibliográficos y audiovisuales de libre acceso en internet; una práctica, de obtención de datos; y una final, de interpretación de los cambios paleoambientales que conlleva la presentación de los resultados en forma de artículo científico y posterior debate en el aula. Todos los datos necesarios para el desarrollo de la actividad se proporcionan en el presente artículo, si bien esta propuesta de taller queda abierta a las posibles modificaciones y mejoras que el profesorado considere oportunas. Para vertebrar esta propuesta, en forma de ejemplo de aplicación, se ha incluido el taller en la programación de la asignatura Biología y Geología (4º ESO). La puesta a punto de este taller pone de manifiesto que resulta idóneo para el trabajo en grupo en el aula permitiendo que el alumnado se sienta partícipe de todas las fases que constituyen una investigación científica.

Improving kNN multi-label classification in Prototype Selection scenarios using class proposals

Prototype Selection (PS) algorithms allow a faster Nearest Neighbor classification by keeping only the most profitable prototypes of the training set. In turn, these schemes typically lower the performance accuracy. In this work a new strategy for multi-label classifications tasks is proposed to solve this accuracy drop without the need of using all the training set. For that, given a new instance, the PS algorithm is used as a fast recommender system which retrieves the most likely classes. Then, the actual classification is performed only considering the prototypes from the initial training set belonging to the suggested classes. Results show that this strategy provides a large set of trade-off solutions which fills the gap between PS-based classification efficiency and conventional kNN accuracy. Furthermore, this scheme is not only able to, at best, reach the performance of conventional kNN with barely a third of distances computed, but it does also outperform the latter in noisy scenarios, proving to be a much more robust approach.

Feature selection by multi-objective optimisation: Application to network anomaly detection by hierarchical self-organising maps

Feature selection is an important and active issue in clustering and classification problems. By choosing an adequate feature subset, a dataset dimensionality reduction is allowed, thus contributing to decreasing the classification computational complexity, and to improving the classifier performance by avoiding redundant or irrelevant features. Although feature selection can be formally defined as an optimisation problem with only one objective, that is, the classification accuracy obtained by using the selected feature subset, in recent years, some multi-objective approaches to this problem have been proposed. These either select features that not only improve the classification accuracy, but also the generalisation capability in case of supervised classifiers, or counterbalance the bias toward lower or higher numbers of features that present some methods used to validate the clustering/classification in case of unsupervised classifiers. The main contribution of this paper is a multi-objective approach for feature selection and its application to an unsupervised clustering procedure based on Growing Hierarchical Self-Organising Maps (GHSOMs) that includes a new method for unit labelling and efficient determination of the winning unit. In the network anomaly detection problem here considered, this multi-objective approach makes it possible not only to differentiate between normal and anomalous traffic but also among different anomalies. The efficiency of our proposals has been evaluated by using the well-known DARPA/NSL-KDD datasets that contain extracted features and labelled attacks from around 2 million connections. The selected feature sets computed in our experiments provide detection rates up to 99.8% with normal traffic and up to 99.6% with anomalous traffic, as well as accuracy values up to 99.12%.

Multiwavelength study of the fast rotating supergiant high-mass X-ray binary IGR J16465−4507

Context. Since its launch, the X-ray and γ-ray observatory INTEGRAL satellite has revealed a new class of high-mass X-ray binaries (HMXB) displaying fast flares and hosting supergiant companion stars. Optical and infrared (OIR) observations in a multi-wavelength context are essential to understand the nature and evolution of these newly discovered celestial objects. Aims. The goal of this multiwavelength study (from ultraviolet to infrared) is to characterise the properties of IGR J16465−4507, to confirm its HMXB nature and that it hosts a supergiant star. Methods. We analysed all OIR, photometric and spectroscopic observations taken on this source, carried out at ESO facilities. Results. Using spectroscopic data, we constrained the spectral type of the companion star between B0.5 and B1 Ib, settling the debate on the true nature of this source. We measured a high rotation velocity of v = 320 ± 8km s-1 from fitting absorption and emission lines in a stellar spectral model. We then built a spectral energy distribution from photometric observations to evaluate the origin of the different components radiating at each energy range. Conclusions. We finally show that, having accurately determined the spectral type of the early-B supergiant in IGR J16465−4507, we firmly support its classification as an intermediate supergiant fast X-ray transient (SFXT).