Recursos de colección

Archivo Digital UPM (115.086 recursos)

This is an institutional repository providing access to the research output of the institution. Primarily contains thesis.

Materia = Matemáticas

Mostrando recursos 1 - 20 de 58

  1. Modelado del campo acústico por los métodos de elementos finitos y elementos de contorno

    Reyes López, Elena de los
    Actualmente los métodos numéricos aplicados a la acústica han supuesto un ahorro considerable, tanto económico como en tiempo de desarrollo, a la hora de hacer estudios acústicos sobre nuevos productos y su entorno. La mejora de los ordenadores, entre otras cosas en capacidad y tiempo de computación, así como la implementación de nuevos algoritmos matemáticos en los paquetes de software que manejan métodos como el de los Elementos Finitos y el de los Elementos de Contorno, ha conseguido que esta sea una herramienta imprescindible para abordar ciertos problemas acústicos. Este proyecto, pretende hacer un breve estudio del campo acústico alrededor de...

  2. Transition state theory for activated systems with driven anharmonic barriers

    Revuelta Peña, Fabio; Craven, Gaten T.; Bartsch, Thomas; Borondo Rodríguez, Florentino; Benito Zafrilla, Rosa Maria
    Classical transition state theory has been extended to address chemical reactions across barriers that are driven and anharmonic. This resolves a challenge to the naive theory that necessarily leads to recrossings and approximate rates because it relies on a fixed dividing surface. We develop both per- turbative and numerical methods for the computation of a time-dependent recrossing-free dividing surface for a model anharmonic system in a solvated environment that interacts strongly with an oscil- latory external field. We extend our previous work, which relied either on a harmonic approximation or on periodic force driving. We demonstrate that the reaction rate,...

  3. Negaciones sobre los grados de pertenencia de los conjuntos borrosos de tipo 2

    Hernández, Pablo; Cubillo Villanueva, Susana; Torres Blanc, Carmen
    Los conjuntos borrosos de tipo 2 (I2FSs) fueron introducidos por L. Zadeh en 1975, como una extensión de los conjuntos borrosos de tipo 1 (FSs). Mientras que en estos ultimos el grado de pertenencia de un elemento al conjunto es un un valor en [0,1 ], en el caso de los T2FSs el grado de pertenencia es una función de [0,1] en [0,1 ]. La unaria operación de negación sobre un conjunto parcialmente ordenado y acotado, se emplea para modelar el complemento de dicho conjunto, y debe satisfacer las propiedades de contomo y ser decreciente. Si ademas es involutiva se...

  4. A methodology for designing automatic evaluators using GLMP paradigm

    Sanchez Torrubia, Maria Gloria; Torres Blanc, Carmen
    Formative assessment enhances human learning processes as it provides learners wiith information about what they need to work on. To automate formative assessment, we built a general model ( GLMP) that allows the design of systems aimed at reproducing instructor's reasoning for learning assessment and generate a natural language assessment report. This paper presents a methodology for designing these automatic evaluators, highlighting the nlain points to be taken into consideration by the designer.

  5. Dynamic Bayesian network-based anomaly detection for in-process visual inspection of laser surface heat treatment

    Ogbechie Condes, Alberto; Díaz Rozo, Javier; Larrañaga Múgica, Pedro María; Bielza Lozoya, María Concepción
    We present the application of a cyber-physical system for inprocess quality control based on the visual inspection of a laser surface heat treatment process. To do this, we propose a classification framework that detects anomalies in recorded video sequences that have been preprocessed using a clustering-based method for feature subset selection. One peculiarity of the classification task is that there are no examples with errors, since major irregularities seldom occur in efficient industrial processes. Additionally, the parts to be processed are expensive so the sample size is small. The proposed framework uses anomaly detection, cross-validation and sampling techniques to deal with these issues. Regarding anomaly detection, dynamic Bayesian networks (DBNs)...

  6. EvalGRAPHs: herramienta para implementar evaluadores inteligentes. Metodología de estudio del comportamiento de los evaluadores

    Sanchez Torrubia, Maria Gloria; Torres Blanc, Carmen; García Guerrero, Silvia; González Martín, Rubén
    El Modelo Granular Lingüístico de la Evaluación del aprendizaje humano ha sido desarrollado a partir del paradigma GLMP, basado en la computación con palabras y percepciones, con el objetivo de diseñar un modelo teórico de representación del aprendizaje que pueda aplicarse a la creación de sistemas (GLMPs) que emulen la evaluación realizada por un profesor, en base a sus criterios, y expresen dicha evaluación mediante un informe en lenguaje natural. Un GLMP es una estructura jerárquica que organiza y procesa datos mediante inferencia borrosa y modela un fenómeno mediante percepciones o unidades de conocimiento. Estos sistemas utilizan como datos de...

  7. Complicity functions for detecting organized crime rings

    Mateos Caballero, Alfonso; Jiménez Martín, Antonio; Vicente Cestero, Eloy
    Graph theory is an evident paradigm for analyzing social networks, which are the main tool for collective behavior research, addressing the interrelations between members of a more or less well-defined community. Particularly, social network analysis has important implications in the fight against organized crime, business associations with fraudulent purposes or terrorism. Classic centrality functions for graphs are able to identify the key players of a network or their intermediaries. However, these functions provide little information in large and heterogeneous graphs. Often the most central elements of the network (usually too many) are not related to a collective of actors of...

  8. Unstable manifold, Conley index and fixed points of flows

    Barge Yáñez, Héctor; Rodríguez Sanjurjo, José Manuel
    We study dynamical and topological properties of the unstable manifold of isolated invariant compacta of flows. We show that some parts of the unstable manifold admit sections carrying a considerable amount of information. These sections enable the construction of parallelizable structures which facilitate the study of the flow. From this fact, many nice consequences are derived, specially in the case of plane continua. For instance, we give an easy method of calculation of the Conley index provided we have some knowledge of the unstable manifold and, as a consequence, a relation between the Brouwer degree and the unstable manifold is...

  9. A MCDA framework for the remediation of zapadnoe uranium mill tailings: a fuzzy approach

    Jiménez Martín, Antonio; Martín Blanco, Miguel Carlos; Pérez-Sánchez, Danyl; Mateos Caballero, Alfonso; Dvorzhak, Alla
    We propose a theoretical framework based on MCDA and fuzzy logic to analyze remediation alternatives for the Zapadnoe uranium mill tailings (Ukraine).We account for potentially conflicting economic, social, radiological and environmental objectives, which are included in an objective hierarchy. Fuzzy rather than precise values are proposed for use to evaluate remediation alternatives against the different criteria and to quantify preferences, such as the weights representing the relative importance of criteria. Remediation alternatives are evaluated by means of a fuzzy additive multi-attribute utility function and ranked on the basis of the similarity of the respective trapezoidal fuzzy number representing their overall utility to the anti-ideal point.

  10. Random positioning of dendritic spines in the human cerebral cortex

    Morales del Olmo, Juan; Benavides Piccione, Ruth; Dar, Mor; Fernaud Espinosa, Isabel; Rodríguez Martínez Bartolomé, Ángel; Antón Sánchez, Laura; Bielza Lozoya, María Concepción; Larrañaga Múgica, Pedro María; Felipe Oroquieta, Javier de; Yuste, Rafael
    Dendritic spines establish most excitatory synapses in the brain and are located in Purkinje cell?s dendrites along helical paths, perhaps maximizing the probability to contact different axons. To test whether spine helixes also occur in neocortex, we reconstructed ?500 dendritic segments from adult human cortex obtained from autopsies. With Fourier analysis and spatial statistics, we analyzed spine position along apical and basal dendrites of layer 3 pyramidal neurons from frontal, temporal, and cingulate cortex. Although we occasionally detected helical positioning, for the great majority of dendrites we could not reject the null hypothesis of spatial randomness in spine locations, either...

  11. A novel multi-dimensional regression model based on Gaussian Networks

    Llera Montero, Milton
    Modeling and prediction in continuous domains are one of the most important and studied problems in Mathematics and Computer Science. Models that can not only solve regression tasks, but also expose the interdependencies inside the domain are of high value for researchers in many fields. One of the most popular methods for learning the relations between variables in a continuous domain are Gaussian Networks. In this thesis we present a new model that can learn a Gaussian Network. This model can later be used for regression or analysis of the relations in the domain, with a particular interest in its application in the field of Neuroscience.---RESUMEN---Modelar y predecir en...

  12. Ann: a domain-specific language for the effective design and validation of Java annotations

    Córdoba Sánchez, Irene; Lara Jaramillo, Juan de
    This paper describes a new modelling language for the effective design and validation of Java annotations. Since their inclusion in the 5th edition of Java, annotations have grown from a useful tool for the addition of meta-data to play a central role in many popular software projects. Usually they are not conceived in isolation, but in groups, with dependency and integrity constraints between them. However, the native support provided by Java for expressing this design is very limited. To over come its deficiencies and make explicit the rich conceptual model which lies behind a set of annotations,we propose a domain-specific modelling language.The proposal has been implemented as an Eclipse plug-in, including an editor and an...

  13. Dendritic-branching angles of pyramidal neurons of the human cerebral cortex

    Fernández González, Pablo; Benavides Piccione, Ruth; Leguey Vitoriano, Ignacio; Bielza Lozoya, María Concepción; Larrañaga Múgica, Pedro María; Felipe Oroquieta, Javier de
    In this article, we analyze branching angles of the basal dendrites of pyramidal neurons of layers III and V of the human temporal cortex. For this, we use a novel probability directional statistical distribution called truncated von Mises distribution that is able to describe more accurately the dendritic-branching angles than the previous proposals. Then, we perform comparative studies using this statistical method to determine similarities and/or differences between branches and branching angles that belong to different cortical layers and regions. Using this methodology, we found that common design principles exist and govern the patterns found in the different branches that compose the basal dendrites of human pyramidal cells of the temporal cortex. However,...

  14. Dominance measuring methods for the selection of cleaning services in a European underground transportation company

    Jiménez Martín, Antonio; Mateos Caballero, Alfonso; Fernández del Pozo de Salamanca, Juan Antonio
    Dominance measuring methods are a recent approach for dealing with complex decisionmaking problems with imprecise, incomplete or partial information within multi-attribute value/utility theory. These methods compute pairwise dominance values and exploit the information included in the dominance matrix in different ways to derive measures of dominance intensity to rank the alternatives under consideration. We review dominance measuring methods proposed in the literature, describing how their possible drawbacks have been progressively overcome, and comparing their performance with other existing approaches, like surrogate weighting methods, the adaptation of classical decision rules to encompass an imprecise decision context, SMAA or Sarabando and Dias’ method. An example of the selection of cleaning...

  15. Multi-facet determination for clustering with Bayesian networks

    Rodríguez-Sánchez, Fernando; Larrañaga Múgica, Pedro; Bielza Lozoya, María Concepción
    Real world applications of sectors like industry, healthcare or finance usually generate data of high complexity that can be interpreted from different viewpoints. When clustering this type of data, a single set of clusters may not suffice, hence the necessity of methods that generate multiple clusterings that represent different perspectives. In this paper, we present a novel multi-partition clustering method that returns several interesting and non-redundant solutions, where each of them is a data partition with an associated facet of data. Each of these facets represents a subset of the original attributes that is selected using our information-theoretic criterion UMRMR. Our approach is based on an optimization...

  16. Learning tractable multidimensional Bayesian network classifiers

    Benjumeda Barquita, Marco Alberto; Larrañaga Múgica, Pedro María; Bielza Lozoya, María Concepción
    Multidimensional classification has become one of the most relevant topics in view of the many domains that require a vector of class values to be assigned to a vector of given features. The popularity of multidimensional Bayesian network classifiers has increased in the last few years due to their expressive power and the existence of methods for learning different families of these models. The problem with this approach is that the computational cost of using the learned models is usually high, especially if there are a lot of class variables. Class-bridge decomposability means that the multidimensional classification problem can be divided into multiple subproblems for these models....

  17. Mining multi-dimensional concept-drifting data streams using Bayesian network classifiers

    Borchani, Hanen; Larrañaga Múgica, Pedro María; Gama, João; Bielza Lozoya, María Concepción
    In recent years, a plethora of approaches have been proposed to deal with the increasingly challenging task of mining concept-drifting data streams. However, most of these approaches can only be applied to uni-dimensional classification problems where each input instance has to be assigned to a single output class variable. The problem of mining multi-dimensional data streams, which includes multiple output class variables, is largely unexplored and only few streaming multi-dimensional approaches have been recently introduced. In this paper, we propose a novel adaptive method, named Locally Adaptive-MB-MBC (LA-MB-MBC), for mining streaming multi-dimensional data. To this end, we make use of multi-dimensional Bayesian network classifiers (MBCs) as...

  18. Data publications correlate with citation impact

    Leitner, Florian; Bielza Lozoya, María Concepción; Hill, Sean L.; Larrañaga Múgica, Pedro María
    Neuroscience and molecular biology have been generating large atasets over the past years that are reshaping how research is being conducted.In their wake, open data sharing has been singled out as a major challenge for the future of research. We conducted a comparative study of citations of data publications in both fields, showing that the average publication tagged with a data-related term by the NCBI MeSH(MedicalSubjectHeadings) curators achieves a significantly larger citation impact than the average in either field. We introduce a new metric, the data article citation index(DAC-index), to identify the most prolific authors among those data-related publications.The study...

  19. Wiring economy of pyramidal cells in the juvenile rat somatosensory cortex

    Antón Sánchez, Laura; Bielza Lozoya, María Concepción; Larrañaga Múgica, Pedro María; Felipe Oroquieta, Javier de
    Ever since Cajal hypothesized that the structure of neurons is designed in such a way as to save space, time and matter, numerous researchers have analyzed wiring properties at different scales of brain organization. Here we test the hypothesis that individual pyramidal cells, the most abundant type of neuron in the cerebral cortex, optimize brain connectivity in terms of wiring length. In this study, we analyze the neuronal wiring of complete basal arborizations of pyramidal neurons in layer II, III, IV, Va, Vb and VI of the hindlimb somatosensory cortical region of postnatal day 14 rats. For each cell, we...

  20. Aplicación de sistemas de control para la recuperación de sistemas de lanzamiento

    Lubián Arenillas, Daniel
    Se aborda el problema del aterrizaje de la primera etapa de un lanzador convencional para su recuperación total, siguiendo una aproximación semejante a la que llevan a cabo compañías del sector privado. Este problema surge de la necesidad de reducir los costes de lanzamiento, de colocación en órbita y de acceso al espacio que los vehículos lanzadores desechables traen consigo. Se construye un modelo matemático sencillo en dos grados de libertad (traslaciones horizontal y vertical) y con un sistema de control vectorial de empuje con fuertes hipótesis simplificatorias con el objetivo de poder observar la física intrínseca al problema con...

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