Aplicación de auto-corrección continua para practicas de análisis de estructuras

The adaptation to the European Higher Educational area is an opportunity to incorporate on-line methods of education assessment in the field of the "Structural Analysis". This paper promotes the intensive use of MOODLE platform of the Technical University of Madrid, to implement the Information and Communication Technology program in this area. This article summarizes the educational experience achieved during the last courses though the use of a new software tool for continuous self-testing by the students. Individualized test are achieved by randomized variable data for each student. Several benefits for the educational purposes have arisen. Firstly, a considerable speeding of the evaluation process, and more than this, a massive input by the students. Certainly, the use of this tool can be very useful for the learning process and therefore for the improvement of the student’s skills and abilities.

Regularized logistic regression and multi-objective variable selection for classifying MEG data

This paper addresses the question of maximizing classifier accuracy for classifying task-related mental activity from Magnetoencelophalography (MEG) data. We propose the use of different sources of information and introduce an automatic channel selection procedure. To determine an informative set of channels, our approach combines a variety of machine learning algorithms: feature subset selection methods, classifiers based on regularized logistic regression, information fusion, and multiobjective optimization based on probabilistic modeling of the search space. The experimental results show that our proposal is able to improve classification accuracy compared to approaches whose classifiers use only one type of MEG information or for which the set of channels is fixed a priori.

Variable Speed Limits. Review and development of an aggregate indicator based on floating car data.

Changing factors (mainly traffic intensity and weather conditions) affecting road conditions require a suitable optimal speed at any time. To solve this problem, variable speed limit systems (VSL) ? as opposed to fixed limits ? have been developed in recent decades. This term has included a number of speed management systems, most notably dynamic speed limits (DSL). In order to avoid the indiscriminate use of both terms in the literature, this paper proposes a simple classification and offers a review of some experiences, how their effects are evaluated and their results This study also presents a key indicator, which measures the speed homogeneity and a methodology to obtain the data based on floating cars and GPS technology applying it to a case study on a section of the M30 urban motorway in Madrid (Spain).

Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data

Mass spectrometry (MS) data provide a promising strategy for biomarker discovery. For this purpose, the detection of relevant peakbins in MS data is currently under intense research. Data from mass spectrometry are challenging to analyze because of their high dimensionality and the generally low number of samples available. To tackle this problem, the scientific community is becoming increasingly interested in applying feature subset selection techniques based on specialized machine learning algorithms. In this paper, we present a performance comparison of some metaheuristics: best first (BF), genetic algorithm (GA), scatter search (SS) and variable neighborhood search (VNS). Up to now, all the algorithms, except for GA, have been first applied to detect relevant peakbins in MS data. All these metaheuristic searches are embedded in two different filter and wrapper schemes coupled with Naive Bayes and SVM classifiers.

Environmental variables modeling based on remote sensing data using time series analysis: forestry and agricultural applications

En la actualidad, el seguimiento de la dinámica de los procesos medio ambientales está considerado como un punto de gran interés en el campo medioambiental. La cobertura espacio temporal de los datos de teledetección proporciona información continua con una alta frecuencia temporal, permitiendo el análisis de la evolución de los ecosistemas desde diferentes escalas espacio-temporales. Aunque el valor de la teledetección ha sido ampliamente probado, en la actualidad solo existe un número reducido de metodologías que permiten su análisis de una forma cuantitativa. En la presente tesis se propone un esquema de trabajo para explotar las series temporales de datos de teledetección, basado en la combinación del análisis estadístico de series de tiempo y la fenometría. El objetivo principal es demostrar el uso de las series temporales de datos de teledetección para analizar la dinámica de variables medio ambientales de una forma cuantitativa. Los objetivos específicos son: (1) evaluar dichas variables medio ambientales y (2) desarrollar modelos empíricos para predecir su comportamiento futuro. Estos objetivos se materializan en cuatro aplicaciones cuyos objetivos específicos son: (1) evaluar y cartografiar estados fenológicos del cultivo del algodón mediante análisis espectral y fenometría, (2) evaluar y modelizar la estacionalidad de incendios forestales en dos regiones bioclimáticas mediante modelos dinámicos, (3) predecir el riesgo de incendios forestales a nivel pixel utilizando modelos dinámicos y (4) evaluar el funcionamiento de la vegetación en base a la autocorrelación temporal y la fenometría. Los resultados de esta tesis muestran la utilidad del ajuste de funciones para modelizar los índices espectrales AS1 y AS2. Los parámetros fenológicos derivados del ajuste de funciones permiten la identificación de distintos estados fenológicos del cultivo del algodón. El análisis espectral ha demostrado, de una forma cuantitativa, la presencia de un ciclo en el índice AS2 y de dos ciclos en el AS1 así como el comportamiento unimodal y bimodal de la estacionalidad de incendios en las regiones mediterránea y templada respectivamente. Modelos autorregresivos han sido utilizados para caracterizar la dinámica de la estacionalidad de incendios y para predecir de una forma muy precisa el riesgo de incendios forestales a nivel pixel. Ha sido demostrada la utilidad de la autocorrelación temporal para definir y caracterizar el funcionamiento de la vegetación a nivel pixel. Finalmente el concepto “Optical Functional Type” ha sido definido, donde se propone que los pixeles deberían ser considerados como unidades temporales y analizados en función de su dinámica temporal. ix SUMMARY A good understanding of land surface processes is considered as a key subject in environmental sciences. The spatial-temporal coverage of remote sensing data provides continuous observations with a high temporal frequency allowing the assessment of ecosystem evolution at different temporal and spatial scales. Although the value of remote sensing time series has been firmly proved, only few time series methods have been developed for analyzing this data in a quantitative and continuous manner. In the present dissertation a working framework to exploit Remote Sensing time series is proposed based on the combination of Time Series Analysis and phenometric approach. The main goal is to demonstrate the use of remote sensing time series to analyze quantitatively environmental variable dynamics. The specific objectives are (1) to assess environmental variables based on remote sensing time series and (2) to develop empirical models to forecast environmental variables. These objectives have been achieved in four applications which specific objectives are (1) assessing and mapping cotton crop phenological stages using spectral and phenometric analyses, (2) assessing and modeling fire seasonality in two different ecoregions by dynamic models, (3) forecasting forest fire risk on a pixel basis by dynamic models, and (4) assessing vegetation functioning based on temporal autocorrelation and phenometric analysis. The results of this dissertation show the usefulness of function fitting procedures to model AS1 and AS2. Phenometrics derived from function fitting procedure makes it possible to identify cotton crop phenological stages. Spectral analysis has demonstrated quantitatively the presence of one cycle in AS2 and two in AS1 and the unimodal and bimodal behaviour of fire seasonality in the Mediterranean and temperate ecoregions respectively. Autoregressive models has been used to characterize the dynamics of fire seasonality in two ecoregions and to forecasts accurately fire risk on a pixel basis. The usefulness of temporal autocorrelation to define and characterized land surface functioning has been demonstrated. And finally the “Optical Functional Types” concept has been proposed, in this approach pixels could be as temporal unities based on its temporal dynamics or functioning.

Agaete revisited: new data on the Gran Canaria tsunamiites.

The tsunami deposits of the valley of Agaete (Pérez-Torrado et al., 2006), north-western Gran Canaria, attributed to the Guimar flank collapse in Tenerife, have been revisited and new data are presented here. Besides the occurrences reported by Pérez-Torrado et al. (2006) a new outcrop was found and named “La Ruina” (at 28º 05’ 47,41” N; 15º 41’ 52,04” W; 71 m asl). The above-mentioned authors suggested the possibility that more than one marine conglomerate deposit could be present in the outcrops of “Llanos de Turmán” and “Berrazales”. At “La Gasolinera” and “La Aldea 1” the conglomerates are formed by a single layer representing one depositional event; at “La Aldea 2”, the conglomerates are composed of two layers directly contacting with each other, but evidence of a time hiatus between them was not found. Although the hypothesis of stacking of two depositional units within the same episode versus deposition of two distinct layers in different time-moments is debatable at the present state of knowledge, the first possibility is favoured. The field evidence at “Llanos de Turman” and “Berrazales” unquestionably shows that terrestrial sediments (colluvia; paleosols) are present and separate two marine conglomerate deposits, indicating that at least two distinct tsunami inundations are needed to explain the stratigraphy. However, at the new “La Ruina” outcrop, besides the two deposits mentioned above, a third and older marine conglomerate was found, clearly separated in time from the ones cited above. The existence of marine conglomerates emplaced in different moments is evidenced by the occurrence of intercalated paleosols, colluvia and other subaerial materials, implying significant time intervals between the emplacement of marine conglomeratic layers. A number of gastropod operculae from the tsunamiites were sent for U-Th dating to try to further constrain the age span of these deposits. The field evidence presented above shows that the emplacement of the deposits is related to, at least, three tsunami events. The lateral correlation between different outcrops is difficult due to variable number of deposits in each outcrop, lateral discontinuity and variability, and to compositional and textural similarity between distinct tsunami sediments. The occurrence of three Pleistocene tsunami deposits in the same area points to a relatively high frequency of tsunamis (generated by landslides, surface rupturing earthquakes, fast entry of voluminous volcanic deposits into the sea or large submarine eruptions). It is possible that this recurrence of tsunami inundations may reflect multiple-phased landslides responsible for the mega-landslide scars prominent in the geomorphology of the neighbouring island of Tenerife. This is a contribution from project “Estabilidad de los edificios volcánicos en Canarias: análisis de los factores geológicos, geomecánicos y paleoclimáticos. Aplicación a los flancos N y S de la isla de Tenerife” financed by MCT, Spain.

Optimización de la Exactitud Geométrica al Integrar Diversas Fuentes de Datos en Proyectos de Inventario Forestal Basados en Escaneo Laser Aerotransportado=Optimizing Geometric Accuracy in Data Source Integration for Airborne Laser Scanning-based Forest Inventory Projects

La mayoría de las aplicaciones forestales del escaneo laser aerotransportado (ALS, del inglés airborne laser scanning) requieren la integración y uso simultaneo de diversas fuentes de datos, con el propósito de conseguir diversos objetivos. Los proyectos basados en sensores remotos normalmente consisten en aumentar la escala de estudio progresivamente a lo largo de varias fases de fusión de datos: desde la información más detallada obtenida sobre un área limitada (la parcela de campo), hasta una respuesta general de la cubierta forestal detectada a distancia de forma más incierta pero cubriendo un área mucho más amplia (la extensión cubierta por el vuelo o el satélite). Todas las fuentes de datos necesitan en ultimo termino basarse en las tecnologías de sistemas de navegación global por satélite (GNSS, del inglés global navigation satellite systems), las cuales son especialmente erróneas al operar por debajo del dosel forestal. Otras etapas adicionales de procesamiento, como la ortorectificación, también pueden verse afectadas por la presencia de vegetación, deteriorando la exactitud de las coordenadas de referencia de las imágenes ópticas. Todos estos errores introducen ruido en los modelos, ya que los predictores se desplazan de la posición real donde se sitúa su variable respuesta. El grado por el que las estimaciones forestales se ven afectadas depende de la dispersión espacial de las variables involucradas, y también de la escala utilizada en cada caso. Esta tesis revisa las fuentes de error posicional que pueden afectar a los diversos datos de entrada involucrados en un proyecto de inventario forestal basado en teledetección ALS, y como las propiedades del dosel forestal en sí afecta a su magnitud, aconsejando en consecuencia métodos para su reducción. También se incluye una discusión sobre las formas más apropiadas de medir exactitud y precisión en cada caso, y como los errores de posicionamiento de hecho afectan a la calidad de las estimaciones, con vistas a una planificación eficiente de la adquisición de los datos. La optimización final en el posicionamiento GNSS y de la radiometría del sensor óptico permitió detectar la importancia de este ultimo en la predicción de la desidad relativa de un bosque monoespecífico de Pinus sylvestris L. ABSTRACT Most forestry applications of airborne laser scanning (ALS) require the integration and simultaneous use of various data sources, pursuing a variety of different objectives. Projects based on remotely-sensed data generally consist in upscaling data fusion stages: from the most detailed information obtained for a limited area (field plot) to a more uncertain forest response sensed over a larger extent (airborne and satellite swath). All data sources ultimately rely on global navigation satellite systems (GNSS), which are especially error-prone when operating under forest canopies. Other additional processing stages, such as orthorectification, may as well be affected by vegetation, hence deteriorating the accuracy of optical imagery’s reference coordinates. These errors introduce noise to the models, as predictors displace from their corresponding response. The degree to which forest estimations are affected depends on the spatial dispersion of the variables involved and the scale used. This thesis reviews the sources of positioning errors which may affect the different inputs involved in an ALS-assisted forest inventory project, and how the properties of the forest canopy itself affects their magnitude, advising on methods for diminishing them. It is also discussed how accuracy should be assessed, and how positioning errors actually affect forest estimation, toward a cost-efficient planning for data acquisition. The final optimization in positioning the GNSS and optical image allowed to detect the importance of the latter in predicting relative density in a monospecific Pinus sylvestris L. forest.

Estudio numérico de flujo turbulento cargado con partículas sólidas a través de canales y tuberías de sección variable

La presente Tesis Doctoral tiene como objetivo el estudio de flujo turbulento cargado con partículas sólidas a través de canales y tuberías de sección constante usando un enfoque Euleriano-Lagrangiano. El campo de flujo de la fase de transporte (aire) se resuelve usando simulación de grandes escalas (LES), implementada en un programa de volúmenes finitos mientras que las ecuaciones gobernantes de la fase dispersa son resueltas por medio de un algoritmo de seguimiento Lagrangiano de partículas que ha sido desarrollado y acoplado al programa que resuelve el flujo. Se estudia de manera sistemática y progresiva la interacción fluido→partícula (one-way coupling), a través de diferentes configuraciones geométricas en coordenadas cartesianas (canales de sección constante y variable) y en coordenadas cilíndricas (tuberías de sección constante y sección variable) abarcando diferentes números de Reynolds y diferentes tamaños de partículas; todos los resultados obtenidos han sido comparados con datos publicados previamente. El estudio de flujo multifásico a través de, tuberías de sección variable, ha sido abordada en otras investigaciones mayoritariamente de forma experimental o mediante simulación usando modelos de turbulencia menos complejos y no mediante LES. El patrón de flujo que se verifica en una tubería con expansión es muy complejo y dicha configuración geométrica se halla en múltiples aplicaciones industriales que involucran el transporte de partículas sólidas, por ello es de gran interés su estudio. Como hecho innovador, en esta tesis no solo se resuelven las estadísticas de velocidad del fluido y las partículas en tuberías con diferentes tamaños de expansión y diferentes regímenes de flujo sino que se caracteriza, usando diversas formulaciones del número de Stokes y el parámetro de arrastre, el ingreso y acumulación de partículas dentro de la zona de recirculación, obteniéndose resultados coincidentes con datos experimentales. ABSTRACT The objective of this Thesis research is to study the turbulent flow laden with solid particles through channels and pipes with using Eulerian-Lagrangian approach. The flow field of the transport phase (air ) is solved using large eddy simulation ( LES ) implemented in a program of finite volume while the governing equations of the dispersed phase are resolved by means of a particle Lagrangian tracking algorithm which was developed and coupled to principal program flow solver . We studied systematically and progressively the fluid interaction → particle ( one- way coupling ) , through different geometric configurations in Cartesian coordinates ( channel with constant and variable section) and in cylindrical coordinates ( pipes with constant section and variable section ) covering different Reynolds numbers and different particle sizes, all results have been compared with previously published data . The study of multiphase flow through, pipes with variable section has been addressed in other investigations predominantly experimentally or by simulation using less complex models and no turbulence by LES. The flow pattern is verified in a pipe expansion is very complex and this geometry is found in many industrial applications involving the transport of solid particles, so it is of great interest to study. As an innovator fact , in this Thesis not only finds fluid velocity statistics and particles with different sizes of pipe expansion and different flow regimes but characterized, using various formulations of the Stokes number and the drag parameter are resolved, the entry and accumulation of particles within the recirculation zone , matching results obtained with experimental data.

Homogeneization effects of variable speed limits.

Changing factors (mainly traffic intensity and weather conditions) affecting road conditions require a suitable optimal speed at any time. To solve this problem, variable speed limit systems (VSL) - as opposed to fixed limits - have been developed in recent decades. This term has included a number of speed management systems, most notably dynamic speed limits (DSL). In order to avoid the indiscriminate use of both terms in the literature, this paper proposes a simple classification and offers a review of some experiences, how their effects are evaluated and their results. This study also presents a key indicator which measures the speed homogeneity and a methodology to obtain the data based on floating cars and GPS technology applying it to a case study on a section of the M30 urban motorway in Madrid (Spain). It also presents the relation between this indicator and road performance and emissions values.

Diseño de receptor de torre central para generación directa de vapor con perfil de potencia variable longitudinal y transversalmente

En este estudio se ha realizado el diseño de un receptor de una central de Torre Central de energía solar para generación directa de vapor, mediante el uso de métodos numéricos, con un perfil de potencia incidente variable longitudinal y transversalmente. Para ello se ha dividido la geometría del receptor según el método de diferencias finitas, y se ha procedido a resolver las ecuaciones del balance de energía. Una vez resuelto el sistema de ecuaciones se dispone de la distribución de temperaturas en el receptor y se puede proceder a analizar los resultados así como a calcular otros datos de interés. ABSTRACT In this study it has been made a Central Receiver Solar Thermal Power Plant’s Receiver design for direct steam production, by using numerical methods, with a variable longitudinally and transversely income solar power profile. With this propose, the receiver’s geometry has been divided using the finite difference method, and the energy balance equations have been solved. Once the equations system has been solved, the receiver´s temperature distribution is known, and you can analyze the results as well as calculate other interesting data.

Bayesian model selection of structural explanatory models: Application to road accident data

Using the Bayesian approach as the model selection criteria, the main purpose in this study is to establish a practical road accident model that can provide a better interpretation and prediction performance. For this purpose we are using a structural explanatory model with autoregressive error term. The model estimation is carried out through Bayesian inference and the best model is selected based on the goodness of fit measures. To cross validate the model estimation further prediction analysis were done. As the road safety measures the number of fatal accidents in Spain, during 2000-2011 were employed. The results of the variable selection process show that the factors explaining fatal road accidents are mainly exposure, economic factors, and surveillance and legislative measures. The model selection shows that the impact of economic factors on fatal accidents during the period under study has been higher compared to surveillance and legislative measures.

Evolution over time of heavy vehicle volume in toll roads: A dynamic panel data to identify key explanatory variables in Spain

Improving the knowledge of demand evolution over time is a key aspect in the evaluation of transport policies and in forecasting future investment needs. It becomes even more critical for the case of toll roads, which in recent decades has become an increasingly common device to fund road projects. However, literature regarding demand elasticity estimates in toll roads is sparse and leaves some important aspects to be analyzed in greater detail. In particular, previous research on traffic analysis does not often disaggregate heavy vehicle demand from the total volume, so that the specific behavioral patternsof this traffic segment are not taken into account. Furthermore, GDP is the main socioeconomic variable most commonly chosen to explain road freight traffic growth over time. This paper seeks to determine the variables that better explain the evolution of heavy vehicle demand in toll roads over time. To that end, we present a dynamic panel data methodology aimed at identifying the key socioeconomic variables that explain the behavior of road freight traffic throughout the years. The results show that, despite the usual practice, GDP may not constitute a suitable explanatory variable for heavy vehicle demand. Rather, considering only the GDP of those sectors with a high impact on transport demand, such as construction or industry, leads to more consistent results. The methodology is applied to Spanish toll roads for the 1990?2011 period. This is an interesting case in the international context, as road freight demand has experienced an even greater reduction in Spain than elsewhere, since the beginning of the economic crisis in 2008.

Explaining light vehicle demand evolution in interurban toll roads: a dynamic panel data analysis in Spain

Tolls have increasingly become a common mechanism to fund road projects in recent decades. Therefore, improving knowledge of demand behavior constitutes a key aspect for stakeholders dealing with the management of toll roads. However, the literature concerning demand elasticity estimates for interurban toll roads is still limited due to their relatively scarce number in the international context. Furthermore, existing research has left some aspects to be investigated, among others, the choice of GDP as the most common socioeconomic variable to explain traffic growth over time. This paper intends to determine the variables that better explain the evolution of light vehicle demand in toll roads throughout the years. To that end, we establish a dynamic panel data methodology aimed at identifying the key socioeconomic variables explaining changes in light vehicle demand over time. The results show that, despite some usefulness, GDP does not constitute the most appropriate explanatory variable, while other parameters such as employment or GDP per capita lead to more stable and consistent results. The methodology is applied to Spanish toll roads for the 1990?2011 period, which constitutes a very interesting case on variations in toll road use, as road demand has experienced a significant decrease since the beginning of the economic crisis in 2008.

Análisis y Diseño de Algoritmos de Control Discreto de Sistemas MIMO Lineales y No Lineales Aplicando Técnicas de Control de Estructura Variable

Dentro de las técnicas de control de procesos no lineales, los controladores de estructura variable con modos deslizantes (VSC-SM en sus siglas en inglés) han demostrado ser una solución robusta, por lo cual han sido ampliamente estudiados en las cuatro últimas décadas. Desde los años ochenta se han presentado varios trabajos enfocados a especificar controladores VSC aplicados a sistemas de tiempo discreto (DVSC), siendo uno de los mayores intereses de análisis obtener las mismas prestaciones de robustez e invarianza de los controladores VSC-SM. El objetivo principal del trabajo de Tesis Doctoral consiste en estudiar, analizar y proponer unos esquemas de diseño de controladores DVSC en procesos multivariable tanto lineales como no lineales. De dicho estudio se propone una nueva filosofía de diseño de superficies deslizantes estables donde se han considerado aspectos hasta ahora no estudiados en el uso de DVSC-SM como son las limitaciones físicas de los actuadores y la dinámica deslizante no ideal. Lo más novedoso es 1) la propuesta de una nueva metodología de diseño de superficies deslizantes aplicadas a sistemas MIMO lineales y la extensión del mismo al caso de sistemas multivariables no lineales y 2) la definición de una nueva ley de alcance y de una ley de control robusta aplicada a sistemas MIMO, tanto lineales como no lineales, incluyendo un esquema de reducción de chattering. Finalmente, con el fin de ilustrar la eficiencia de los esquemas presentados, se incluyen ejemplos numéricos relacionados con el tema tratado en cada uno de los capítulos de la memoria. ABSTRACT Over the last four decades, variable structure controllers with sliding mode (VSC-SM) have been extensively studied, demonstrating to be a robust solution among robust nonlinear processes control techniques. Since the late 80s, several research works have been focused on the application of VSC controllers applied to discrete time or sampled data systems, which are known as DVSC-SM, where the most extensive source of analysis has been devoted to the robustness and invariance properties of VSC-SM controllers when applied to discrete systems. The main aim of this doctoral thesis work is to study, analyze and propose a design scheme of DVSC-SM controllers for lineal and nonlinear multivariable discrete time processes. For this purpose, a new design philosophy is proposed, where various design features have been considered that have not been analyzed in DVSC design approaches. Among them, the physical limitations and the nonideal dynamic sliding mode dynamics. The most innovative aspect is the inclusion of a new design methodology applied to lineal sliding surfaces MIMO systems and the extension to nonlinear multivariable systems, in addition to a new robust control law applied to lineal and nonlinear MIMO systems, including a chattering reduction scheme. Finally, to illustrate the efficiency of the proposed schemes, several numerical examples applied to lineal and nonlinear systems are included.