ICGE: an R package for detecting relevant clusters and atypical units in gene expression

Background: Gene expression technologies have opened up new ways to diagnose and treat cancer and other diseases. Clustering algorithms are a useful approach with which to analyze genome expression data. They attempt to partition the genes into groups exhibiting similar patterns of variation in expression level. An important problem associated with gene classification is to discern whether the clustering process can find a relevant partition as well as the identification of new genes classes. There are two key aspects to classification: the estimation of the number of clusters, and the decision as to whether a new unit (gene, tumor sample ... ) belongs to one of these previously identified clusters or to a new group. Results: ICGE is a user-friendly R package which provides many functions related to this problem: identify the number of clusters using mixed variables, usually found by applied biomedical researchers; detect whether the data have a cluster structure; identify whether a new unit belongs to one of the pre-identified clusters or to a novel group, and classify new units into the corresponding cluster. The functions in the ICGE package are accompanied by help files and easy examples to facilitate its use. Conclusions: We demonstrate the utility of ICGE by analyzing simulated and real data sets. The results show that ICGE could be very useful to a broad research community.

A framework for abstraction and virtualization of sensors in mobile context-aware computing

110 p.

On the Informational Role of Term Structure in the U.S. Monetary Policy Rule

This paper uses a structural approach based on the indirect inference principle to estimate a standard version of the new Keynesian monetary (NKM) model augmented with term structure using both revised and real-time data. The estimation results show that the term spread and policy inertia are both important determinants of the U.S. estimated monetary policy rule whereas the persistence of shocks plays a small but significant role when revised and real-time data of output and inflation are both considered. More importantly, the relative importance of term spread and persistent shocks in the policy rule and the shock transmission mechanism drastically change when it is taken into account that real-time data are not well behaved.

Advances towards behaviour-based indoor robotic exploration

215 p.

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.

Herramienta software para el análisis de rendimiento de redes 4G

[ES]El objetivo de este proyecto ha sido desarrollar una herramienta software que permita medir el rendimiento de redes con tecnología móvil 4G, también conocida como LTE. Para ello se ha creado un sistema software que está compuesto por una aplicación móvil y un servidor de aplicaciones. El sistema en conjunto realiza la función de recoger indicadores de calidad de la red móvil de diversa índole, que posteriormente son procesados utilizando herramientas software matemáticas, para así obtener gráficas y mapas que permiten analizar la situación y el rendimiento de una red 4G concreta. El desarrollo del software ha llegado a nivel de prototipo y se han realizado pruebas reales con él obteniendo resultados positivos de funcionamiento.

Estudio empírico homologable del Servicio Municipal de Deportes de Santurtzi

[ES] En este trabajo presentamos un estudio empírico homologable del Instituto Municipal de Deportes de Santurtzi, en el cual se analizan las características y evolución del deporte en este municipio, el nivel de autofinanciación del servicio, el conocimiento de las diferentes instalaciones deportivas, etc. En definitiva, el estudio trata de profundizar en la gestión deportiva del Municipio de Santurtzi, para ello, se emplea un cuestionario específico en el que l obtenemos datos concretos y reales sobre las variables económicas, sociales, técnicas y de Recursos Humanos. Con los datos y resultados de las variables se consigue que al final del estudio se llegue a conclusiones que permitan la autoevaluación en el transcurso del tiempo y la valoración comparada, con municipios de similares características.