Model of sources: a proposal for the hierarchy, merging strategy and representation of the information sources in virtual models of historical buildings

Contributed to: Fusion of Cultures: XXXVIII Annual Conference on Computer Applications and Quantitative Methods in Archaeology – CAA2010 (Granada, Spain, Apr 6-9, 2010)

Algorithms for colour image processing based on neurological models

373 p. : il., gráf., fot., tablas

A review of travel time estimation and forecasting for advanced traveler information systems

Providing on line travel time information to commuters has become an important issue for Advanced Traveler Information Systems and Route Guidance Systems in the past years, due to the increasing traffic volume and congestion in the road networks. Travel time is one of the most useful traffic variables because it is more intuitive than other traffic variables such as flow, occupancy or density, and is useful for travelers in decision making. The aim of this paper is to present a global view of the literature on the modeling of travel time, introducing crucial concepts and giving a thorough classification of the existing tech- niques. Most of the attention will focus on travel time estimation and travel time prediction, which are generally not presented together. The main goals of these models, the study areas and methodologies used to carry out these tasks will be further explored and categorized.

Practical applications of the likelihood, time transcendence and metadata in virtual models of heritage elements

Contributed to: III Bienal de Restauración Monumental: "Sobre la des-restauración" (Sevilla, Spain, Nov 23-25, 2006)

Time transcendence, metadata and future utilization in 3D models of point clouds for heritage elements

Contributed to: Virtual Retrospect 2007 (Pessac, France, Nov 14-16, 2007)

Avances en algoritmos de estimación de distribuciones. Alternativas en el aprendizaje y representación de problemas

131 p.: graf.

Estudio del comportamiento térmico del instrumento TriboLAB durante su estancia en la Estación Espacial Internacional desde la perspectiva del análisis de datos funcionales

[ES]El objetivo principal de esta tesis de máster es el estudio del comportamiento térmico del instrumento TriboLAB durante su estancia en la Estación Espacial Internacional, junto con la comparación de dicho comportamiento con el pronosticado por los modelos térmicos matemáticos empleados en el diseño de su sistema de control térmico. El trabajo realizado ha permitido profundizar de forma importante en el conocimiento del mencionado comportamiento. Ello permitirá poner a disposición de otros experimentadores interesados en ubicar sus instrumentos en los balcones exteriores de la Estación Espacial Internacional, información real acerca del comportamiento térmico de un equipo de las características del TriboLAB en dichas condiciones. Información de gran interés para ser empleada en el diseño del control térmico de sus instrumentos, especialmente ahora que la vida útil de la Estación Espacial Internacional ha sido prorrogada hasta 2020. El control térmico de los equipos espaciales es un aspecto clave para asegurar su supervivencia y correcto funcionamiento bajo las extremas condiciones existentes en el espacio. Su misión es mantener los distintos componentes dentro de su rango de temperaturas admisibles, puesto que en caso contrario no podrían funcionar o incluso ni siquiera sobrevivir más allá de esas temperaturas. Adicionalmente ha sido posible comprobar la aplicabilidad de distintas técnicas de análisis de datos funcionales en lo que respecta al estudio del tipo de datos aquí contemplado. Así mismo, se han comparado los resultados de la campaña de ensayos térmicos con los modelos térmicos matemáticos que han guiado el diseño del control térmico, y que son una pieza fundamental en el diseño del control térmico de cualquier instrumento espacial. Ello ha permitido verificar tanto la validez del sistema de control térmico diseñado para el TriboLAB como con la adecuada similitud existente entre los resultados de los modelos térmicos matemáticos y las temperaturas registradas en el equipo. Todo ello, ha sido realizado desde la perspectiva del análisis de datos funcionales.

Energy and information in Hodgkin-Huxley neurons

[EN]The generation of spikes by neurons is energetically a costly process and the evaluation of the metabolic energy required to maintain the signaling activity of neurons a challenge of practical interest. Neuron models are frequently used to represent the dynamics of real neurons but hardly ever to evaluate the electrochemical energy required to maintain that dynamics. This paper discusses the interpretation of a Hodgkin-Huxley circuit as an energy model for real biological neurons and uses it to evaluate the consumption of metabolic energy in the transmission of information between neurons coupled by electrical synapses, i.e., gap junctions. We show that for a single postsynaptic neuron maximum energy efficiency, measured in bits of mutual information per molecule of adenosine triphosphate (ATP) consumed, requires maximum energy consumption. For groups of parallel postsynaptic neurons we determine values of the synaptic conductance at which the energy efficiency of the transmission presents clear maxima at relatively very low values of metabolic energy consumption. Contrary to what could be expected, the best performance occurs at a low energy cost.

Efficient learning of decomposable models with a bounded clique size

The learning of probability distributions from data is a ubiquitous problem in the fields of Statistics and Artificial Intelligence. During the last decades several learning algorithms have been proposed to learn probability distributions based on decomposable models due to their advantageous theoretical properties. Some of these algorithms can be used to search for a maximum likelihood decomposable model with a given maximum clique size, k, which controls the complexity of the model. Unfortunately, the problem of learning a maximum likelihood decomposable model given a maximum clique size is NP-hard for k > 2. In this work, we propose a family of algorithms which approximates this problem with a computational complexity of O(k · n^2 log n) in the worst case, where n is the number of implied random variables. The structures of the decomposable models that solve the maximum likelihood problem are called maximal k-order decomposable graphs. Our proposals, called fractal trees, construct a sequence of maximal i-order decomposable graphs, for i = 2, ..., k, in k − 1 steps. At each step, the algorithms follow a divide-and-conquer strategy based on the particular features of this type of structures. Additionally, we propose a prune-and-graft procedure which transforms a maximal k-order decomposable graph into another one, increasing its likelihood. We have implemented two particular fractal tree algorithms called parallel fractal tree and sequential fractal tree. These algorithms can be considered a natural extension of Chow and Liu’s algorithm, from k = 2 to arbitrary values of k. Both algorithms have been compared against other efficient approaches in artificial and real domains, and they have shown a competitive behavior to deal with the maximum likelihood problem. Due to their low computational complexity they are especially recommended to deal with high dimensional domains.

Problems when generating virtual models representing real objects: Hondarribia walls

[EN] This paper is based in the following project:

Hunting spectro-temporal information in unevenly spaced paleoclimate time series

18 p.

Countervailing incentives in adverse selection models. A synthesis

In this paper we propose a simple method of characterizing countervailing incentives in adverse selection problems. The key element in our characterization consists of analyzing properties of the full information problem. This allows solving the principal problem without using optimal control theory. Our methodology can also be applied to different economic settings: health economics, monopoly regulation, labour contracts, limited liabilities and environmental regulation.

Combination of web usage, content and structure information for diverse web mining applications in the tourism context and the context of users with disabilities

188 p.

Frame-level features conveying phonetic information for language and speaker recognition

150 p.

Contributions to learning Bayesian network models from weakly supervised data: Application to Assisted Reproductive Technologies and Software Defect Classification

162 p.