On the equivalence between compromise programming and the use of composite compromise metrics.

This paper analyzes the relationship between Compromise Programming and a close relative called Composite Programming that is based on the use of composite metrics. More specifically, it focuses on the possibility that the results of Compromise Programming are equivalent to those obtained with a particular case of Composite Programming in which a linear combination between the two bounds of the compromise set is established. Several situations, depending on the number of criteria involved and the mathematical structure of the efficient set, are studied. The most relevant result is obtained when two criteria are involved and the efficient set is continuously differentiable. In this case, it is possible to find a unique equivalent value of the control parameter in Composite Programming for each metric in Compromise Programming. It is remarked that this particular case is very relevant in many economic scenarios. On the other hand, it turns out that the equivalence between both approaches can not be extended to the case with more than two criteria.Compromise programming, composite metric, p-norms, economic optimization.

A goal programming approach for a joint design of macroeconomic and environmental policies: a methodological proposal and an application to the spanish economy

Economic policy needs to pay more attention to environmental issues. This calls for the development of methodologies capable of incorporating environmental as well as macroeconomic goals in the design of public policies. In view of this, this paper proposes a methodology based upon Simonian satisficing logic implemented with the help of goal programming models to address the joint design of macroeconomic and environmental policies. The methodology is applied to the Spanish economy, where a joint policy is elicited, taking into account macroeconomic goals (economic growth, inflation, unemployment, public deficit) and environmental goals (CO2, NOx and SOx emissions) within the context of a computable general equilibrium model.Environmental policies, goal programming, macroeconomic policies, computable general equilibrium model, multiple criteria decision making, satisficing logic.

Spain and the First World War : neutrality and crisis.

PhDThe subject of this thesis is a study of Spain during the First World War. The Spanish case is analyzed as the regional version of the general crisis which engulfed the rest of Europe during these years. This crisis was produced by the ideological militancy and social struggle caused by four years of devastating international conflict. It heralded the arrival of mass politics which put an end to a previous era marked by hierarchical and clientelist politics. This thesis examines how the maintenance of strict neutrality did not save the existing regime in Spain from the impact of the conflict raging in Europe. Spain did not enter the war but the war entered the country and, ironically, a conflict in which Spain did not take part was to alter its contemporary history. The analysis explores the gradual disintegration of the foundations of the ruling system, the Liberal Monarchy restored in December 1874, during and as a consequence of the First World War. Considerable attention is paid to the impact and importance of the war in producing the decay of the Liberal Monarchy. This process is examined at two levels: the political polarization and subsequent division of the country which was provoked by the debate about belligerence or neutrality, and the social and economic transformations that Spain underwent as consequence a of its privileged position as a supplier to both sides. The result was galloping inflation, widespread social discontent and political turmoil. Under these pressures, the hegemonic system, based on electoral falsification, widespread patronage and mass apathy, collapsed and gave way to an inexorable process of growing working class and right-wing militancy which led to the military coup of 1923

Contribuciones al uso de marcadores para Navegación Autónoma y Realidad Aumentada

Square planar markers are a widely used tools for localization and tracking due to their low cost and high performance. Many applications in Robotics, Unmanned Vehicles and Augmented Reality employ these markers for camera pose estimation with high accuracy. Nevertheless, marker-based systems are affected by several factors that limit their performance. First, the marker detection process is a time-consuming task, which is intensified as the image size increases. As a consequence, the current high-resolution cameras has weakened the processing efficiency of traditional marker systems. Second, marker detection is affected by the presence of noise, blurring and occlusion. The movement of the camera produces image blurriness, generated even by small movements. Furthermore, the marker may be partially or completely occluded in the image, so that it is no longer detected. This thesis deals with the above limitations, proposing novel methodologies and strategies for successful marker detection improving both the efficiency and robustness of these systems. First, a novel multi-scale approach has been developed to speed up the marker detection process. The method takes advantage of the different resolutions at which the image is represented to predict at runtime the optimal scale for detection and identification, as well as following a corner upsampling strategy necessary for an accurate pose estimation. Second, we introduce a new marker design, Fractal Marker, which using a novel keypoint-based method achieves detection even under severe occlusion, while allowing detection over a wider range of distance than traditional markers. Finally, we propose a new marker detection strategy based on Discriminative Correlation Filters (DCF), where the marker and its corners represented in the frequency domain perform more robust and faster detections than state-ofthe- art methods, even under extreme blur conditions.Los marcadores planos cuadrados son una de las herramientas ampliamente utilizadas para la localización y el tracking debido a su bajo coste y su alto rendimiento. Muchas aplicaciones en Robótica, Vehículos no Tripulados y Realidad Aumentada emplean estos marcadores para estimar con alta precisión la posición de la cámara. Sin embargo, los sistemas basados en marcadores se ven afectados por varios factores que limitan su rendimiento. En primer lugar, el proceso de detección de marcadores es una tarea que requiere mucho tiempo y este incrementa a medida que aumenta el tamaño de la imagen. En consecuencia, las actuales cámaras de alta resolución han debilitado la eficacia del procesamiento de los sistemas de marcadores tradicionales. Por otra parte, la detección de marcadores se ve afectada por la presencia de ruido, desenfoque y oclusión. El movimiento de la cámara produce desenfoque de la imagen, generado incluso por pequeños movimientos. Además, el marcador puede aparecer en la imagen parcial o completamente ocluido, dejando de ser detectado. Esta tesis aborda las limitaciones anteriores, proponiendo metodologías y estrategias novedosas para la correcta detección de marcadores, mejorando así tanto la eficiencia como la robustez de estos sistemas. En primer lugar, se ha desarrollado un novedoso enfoque multiescala para acelerar el proceso de detección de marcadores. El método aprovecha las diferentes resoluciones en las que la imagen está representada para predecir en tiempo de ejecución la escala óptima para la detección e identificación, a la vez que sigue una estrategia de upsampling de las esquinas necesaria para estimar la pose con precisión. En segundo lugar, introducimos un nuevo diseño de marcador, Fractal Marker, que, mediante un método basado en keypoints, logra detecciones incluso en casos de oclusión extrema, al tiempo que permite la detección en un rango de distancias más amplio que los marcadores tradicionales. Por último, proponemos una nueva estrategia de detección de marcadores basada en Discriminate Correlation Filters (DCF), donde el marcador y sus esquinas representadas en el dominio de la frecuencia realizan detecciones más robustas y rápidas que los métodos de referencia, incluso bajo condiciones extremas de emborronamiento

3D human pose estimation from depth maps using a deep combination of poses

Many real-world applications require the estimation of human body joints for higher-level tasks as, for example, human behaviour understanding. In recent years, depth sensors have become a popular approach to obtain three-dimensional information. The depth maps generated by these sensors provide information that can be employed to disambiguate the poses observed in two-dimensional images. This work addresses the problem of 3D human pose estimation from depth maps employing a Deep Learning approach. We propose a model, named Deep Depth Pose (DDP), which receives a depth map containing a person and a set of predefined 3D prototype poses and returns the 3D position of the body joints of the person. In particular, DDP is defined as a ConvNet that computes the specific weights needed to linearly combine the prototypes for the given input. We have thoroughly evaluated DDP on the challenging 'ITOP' and 'UBC3V' datasets, which respectively depict realistic and synthetic samples, defining a new state-of-the-art on them.Comment: Accepted for publication at "Journal of Visual Communication and Image Representation

Diffusion in a class of exactly solvable non-harmonic potentials. Intrinsic effects induced by non-linearities

This paper deals with the problem of a particle that diffuses in a potential with a reflecting barrier and has a point of stable equilibrium and a point of unstable equilibrium. Based on the exact solutions obtained earlier for the Fokker-Planck equation of a class of these models, we analyze the behavior of the probability density, the mean path and the onset time which determines the transition from unimodal to bimodal probability densities. The study is made over different initial positions, two of them very close to the unstable point, which permits a clear comparison among the subsequent evolutions, and the observation of some intrinsic effects induced by non-linearities