Diseño de una infraestructura TIC basada en virtualización

[ES] Las necesidades básicas de las empresas suelen ser las mismas, ya sea una empresa grande que pequeña, la infraestructura sobre la que montan sus procesos de negocio y las aplicaciones para gestionarlos suelen ser casi iguales. Si dividimos la infraestructura TIC de una empresa en hardware, sistema y aplicaciones, podemos ver que en la mayoría de ellas el sistema es casi idéntico. Además, gracias a la virtualización, que ha entrado de manera arrolladora en el mundo de la informática, podemos independizar totalmente el software del hardware, de forma que obtenemos una flexibilidad enorme a la hora de planificar despliegues de infraestructura. Sobre estas dos ideas, uniformidad de sistema e independencia de hardware, son sobre las que se va a desarrollar el siguiente TFG. Para el desarrollo de la primera de ellas se realizará el estudio de la infraestructura básica ( sistema) que cualquier empresa suele tener. Se intentará dar una solución que sea válida para una gran cantidad de empresas de nuestro entorno y se realizará el diseño del mismo. Con la segunda idea desarrollaremos un sistema basado en servicios, que sea lo suficientemente completa para poder dar respuesta a las necesidades vistas pero, a su vez, suficientemente flexible para que el crecimiento en capacidades o servicios se pueda realizar de forma sencilla sin que la estructura del sistema, o sus módulos deban modificarse para realizarlos. Por tanto, vamos a realizar un diseño integral y completa, de forma que será tanto de hardware como de software, haciendo énfasis en la integración de los sistemas y la interrelación entre los distintos elementos de ellos. Se dará, a su vez, la valoración económica del mismo. Por último, y como ejemplo de la flexibilidad del diseño elegido veremos dos modificaciones sobre el diseño original. El primero de ellos será una ampliación para dar mayor seguridad en cuanto a redundancia de almacenamiento y, ya en un paso definitivo, montar un CPD remoto. El segundo de ellos será un diseño de bajo coste, en el que, mantenimiento los mismos servicios, bajaremos el coste del diseño con productos con algo menos de prestaciones, pero manteniendo la solución en conjunto unos altos niveles de calidad y servicio.

A partial dependence factorial analysis to deal with selection bias in observational studis

This thesis presents a creative and practical approach to dealing with the problem of selection bias. Selection bias may be the most important vexing problem in program evaluation or in any line of research that attempts to assert causality. Some of the greatest minds in economics and statistics have scrutinized the problem of selection bias, with the resulting approaches – Rubin’s Potential Outcome Approach(Rosenbaum and Rubin,1983; Rubin, 1991,2001,2004) or Heckman’s Selection model (Heckman, 1979) – being widely accepted and used as the best fixes. These solutions to the bias that arises in particular from self selection are imperfect, and many researchers, when feasible, reserve their strongest causal inference for data from experimental rather than observational studies. The innovative aspect of this thesis is to propose a data transformation that allows measuring and testing in an automatic and multivariate way the presence of selection bias. The approach involves the construction of a multi-dimensional conditional space of the X matrix in which the bias associated with the treatment assignment has been eliminated. Specifically, we propose the use of a partial dependence analysis of the X-space as a tool for investigating the dependence relationship between a set of observable pre-treatment categorical covariates X and a treatment indicator variable T, in order to obtain a measure of bias according to their dependence structure. The measure of selection bias is then expressed in terms of inertia due to the dependence between X and T that has been eliminated. Given the measure of selection bias, we propose a multivariate test of imbalance in order to check if the detected bias is significant, by using the asymptotical distribution of inertia due to T (Estadella et al. 2005) , and by preserving the multivariate nature of data. Further, we propose the use of a clustering procedure as a tool to find groups of comparable units on which estimate local causal effects, and the use of the multivariate test of imbalance as a stopping rule in choosing the best cluster solution set. The method is non parametric, it does not call for modeling the data, based on some underlying theory or assumption about the selection process, but instead it calls for using the existing variability within the data and letting the data to speak. The idea of proposing this multivariate approach to measure selection bias and test balance comes from the consideration that in applied research all aspects of multivariate balance, not represented in the univariate variable- by-variable summaries, are ignored. The first part contains an introduction to evaluation methods as part of public and private decision process and a review of the literature of evaluation methods. The attention is focused on Rubin Potential Outcome Approach, matching methods, and briefly on Heckman’s Selection Model. The second part focuses on some resulting limitations of conventional methods, with particular attention to the problem of how testing in the correct way balancing. The third part contains the original contribution proposed , a simulation study that allows to check the performance of the method for a given dependence setting and an application to a real data set. Finally, we discuss, conclude and explain our future perspectives.

Displacement Analysis of Under-Constrained Cable-Driven Parallel Robots

This dissertation studies the geometric static problem of under-constrained cable-driven parallel robots (CDPRs) supported by n cables, with n ≤ 6. The task consists of determining the overall robot configuration when a set of n variables is assigned. When variables relating to the platform posture are assigned, an inverse geometric static problem (IGP) must be solved; whereas, when cable lengths are given, a direct geometric static problem (DGP) must be considered. Both problems are challenging, as the robot continues to preserve some degrees of freedom even after n variables are assigned, with the final configuration determined by the applied forces. Hence, kinematics and statics are coupled and must be resolved simultaneously. In this dissertation, a general methodology is presented for modelling the aforementioned scenario with a set of algebraic equations. An elimination procedure is provided, aimed at solving the governing equations analytically and obtaining a least-degree univariate polynomial in the corresponding ideal for any value of n. Although an analytical procedure based on elimination is important from a mathematical point of view, providing an upper bound on the number of solutions in the complex field, it is not practical to compute these solutions as it would be very time-consuming. Thus, for the efficient computation of the solution set, a numerical procedure based on homotopy continuation is implemented. A continuation algorithm is also applied to find a set of robot parameters with the maximum number of real assembly modes for a given DGP. Finally, the end-effector pose depends on the applied load and may change due to external disturbances. An investigation into equilibrium stability is therefore performed.

Differences in water release for the binding of EcoRI to specific and nonspecific DNA sequences.

The free energy difference between complexes of the restriction nuclease EcoRI with nonspecific DNA and with the enzyme's recognition sequence is linearly dependent on the water chemical potential of the solution, set using several very different solutes, ranging from glycine and glycerol to triethylene glycol and sucrose. This osmotic dependence indicates that the nonspecific complex sequesters some 110 waters more than the specific complex with the recognition sequence. The insensitivity of the difference in number of waters released to the solute identity further indicates that this water is sequestered in a space that is sterically inaccessible to solutes, most likely at the protein-DNA interface of the nonspecific complex. Calculations based on the structure of the specific complex suggest that the apposing DNA and protein surfaces in the nonspecific complex retain approximately a full hydration layer of water.

Global behavior of positive solutions of nonlinear three-point boundary value problems

We investigate the structure of the positive solution set for nonlinear three-point boundary value problems of the form u('') + h(t) f(u) = 0, u(0) = 0, u(1) = lambdau(eta), where eta epsilon (0, 1) is given lambda epsilon (0, 1/n) is a parameter, f epsilon C ([0, infinity), [0, infinity)) satisfies f (s) > 0 for s > 0, and h epsilon C([0, 1], [0, infinity)) is not identically zero on any subinterval of [0, 1]. Our main results demonstrate the existence of continua of positive solutions of the above problem. (C) 2004 Elsevier Ltd. All rights reserved.

Primary students’ interpretation of maps : gesture use and mapping knowledge

Maps are used to represent three-dimensional space and are integral to a range of everyday experiences. They are increasingly used in mathematics, being prominent both in school curricula and as a form of assessing students understanding of mathematics ideas. In order to successfully interpret maps, students need to be able to understand that maps: represent space, have their own perspective and scale, and their own set of symbols and texts. Despite the fact that maps have an increased prevalence in society and school, there is evidence to suggest that students have difficulty interpreting maps. This study investigated 43 primary-aged students’ (aged 9-12 years) verbal and gestural behaviours as they engaged with and solved map tasks. Within a multiliteracies framework that focuses on spatial, visual, linguistic, and gestural elements, the study investigated how students interpret map tasks. Specifically, the study sought to understand students’ skills and approaches used to solving map tasks and the gestural behaviours they utilised as they engaged with map tasks. The investigation was undertaken using the Knowledge Discovery in Data (KDD) design. The design of this study capitalised on existing research data to carry out a more detailed analysis of students’ interpretation of map tasks. Video data from an existing data set was reorganised according to two distinct episodes—Task Solution and Task Explanation—and analysed within the multiliteracies framework. Content Analysis was used with these data and through anticipatory data reduction techniques, patterns of behaviour were identified in relation to each specific map task by looking at task solution, task correctness and gesture use. The findings of this study revealed that students had a relatively sound understanding of general mapping knowledge such as identifying landmarks, using keys, compass points and coordinates. However, their understanding of mathematical concepts pertinent to map tasks including location, direction, and movement were less developed. Successful students were able to interpret the map tasks and apply relevant mathematical understanding to navigate the spatial demands of the map tasks while the unsuccessful students were only able to interpret and understand basic map conventions. In terms of their gesture use, the more difficult the task, the more likely students were to exhibit gestural behaviours to solve the task. The most common form of gestural behaviour was deictic, that is a pointing gesture. Deictic gestures not only aided the students capacity to explain how they solved the map tasks but they were also a tool which assisted them to navigate and monitor their spatial movements when solving the tasks. There were a number of implications for theory, learning and teaching, and test and curriculum design arising from the study. From a theoretical perspective, the findings of the study suggest that gesturing is an important element of multimodal engagement in mapping tasks. In terms of teaching and learning, implications include the need for students to utilise gesturing techniques when first faced with new or novel map tasks. As students become more proficient in solving such tasks, they should be encouraged to move beyond a reliance on such gesture use in order to progress to more sophisticated understandings of map tasks. Additionally, teachers need to provide students with opportunities to interpret and attend to multiple modes of information when interpreting map tasks.

Topological structure of vortex solution in Jackiw-Pi model

By using phi-mapping method, we discuss the topological structure of the self-duality solution in Jackiw-Pi model in terms of gauge potential decomposition. We set up relationship between Chern-Simons vortex solution and topological number, which is determined by Hopf index and Brouwer degree. We also give the quantization of flux in this case. Then, we study the angular momentum of the vortex, which can be expressed in terms of the flux.

Mapping Parallel Iterative Algorithms onto Workstation Networks

For communication-intensive parallel applications, the maximum degree of concurrency achievable is limited by the communication throughput made available by the network. In previous work [HPS94], we showed experimentally that the performance of certain parallel applications running on a workstation network can be improved significantly if a congestion control protocol is used to enhance network performance. In this paper, we characterize and analyze the communication requirements of a large class of supercomputing applications that fall under the category of fixed-point problems, amenable to solution by parallel iterative methods. This results in a set of interface and architectural features sufficient for the efficient implementation of the applications over a large-scale distributed system. In particular, we propose a direct link between the application and network layer, supporting congestion control actions at both ends. This in turn enhances the system's responsiveness to network congestion, improving performance. Measurements are given showing the efficacy of our scheme to support large-scale parallel computations.

QUADrATiC: scalable gene expression connectivity mapping for repurposing FDA-approved therapeutics

Background: Gene expression connectivity mapping has proven to be a powerful and flexible tool for research. Its application has been shown in a broad range of research topics, most commonly as a means of identifying potential small molecule compounds, which may be further investigated as candidates for repurposing to treat diseases. The public release of voluminous data from the Library of Integrated Cellular Signatures (LINCS) programme further enhanced the utilities and potentials of gene expression connectivity mapping in biomedicine. Results: We describe QUADrATiC (http://go.qub.ac.uk/QUADrATiC), a user-friendly tool for the exploration of gene expression connectivity on the subset of the LINCS data set corresponding to FDA-approved small molecule compounds. It enables the identification of compounds for repurposing therapeutic potentials. The software is designed to cope with the increased volume of data over existing tools, by taking advantage of multicore computing architectures to provide a scalable solution, which may be installed and operated on a range of computers, from laptops to servers. This scalability is provided by the use of the modern concurrent programming paradigm provided by the Akka framework. The QUADrATiC Graphical User Interface (GUI) has been developed using advanced Javascript frameworks, providing novel visualization capabilities for further analysis of connections. There is also a web services interface, allowing integration with other programs or scripts.Conclusions: QUADrATiC has been shown to provide an improvement over existing connectivity map software, in terms of scope (based on the LINCS data set), applicability (using FDA-approved compounds), usability and speed. It offers potential to biological researchers to analyze transcriptional data and generate potential therapeutics for focussed study in the lab. QUADrATiC represents a step change in the process of investigating gene expression connectivity and provides more biologically-relevant results than previous alternative solutions.

Efficient topology estimation for large scale optical mapping

Large scale image mosaicing methods are in great demand among scientists who study different aspects of the seabed, and have been fostered by impressive advances in the capabilities of underwater robots in gathering optical data from the seafloor. Cost and weight constraints mean that lowcost Remotely operated vehicles (ROVs) usually have a very limited number of sensors. When a low-cost robot carries out a seafloor survey using a down-looking camera, it usually follows a predetermined trajectory that provides several non time-consecutive overlapping image pairs. Finding these pairs (a process known as topology estimation) is indispensable to obtaining globally consistent mosaics and accurate trajectory estimates, which are necessary for a global view of the surveyed area, especially when optical sensors are the only data source. This thesis presents a set of consistent methods aimed at creating large area image mosaics from optical data obtained during surveys with low-cost underwater vehicles. First, a global alignment method developed within a Feature-based image mosaicing (FIM) framework, where nonlinear minimisation is substituted by two linear steps, is discussed. Then, a simple four-point mosaic rectifying method is proposed to reduce distortions that might occur due to lens distortions, error accumulation and the difficulties of optical imaging in an underwater medium. The topology estimation problem is addressed by means of an augmented state and extended Kalman filter combined framework, aimed at minimising the total number of matching attempts and simultaneously obtaining the best possible trajectory. Potential image pairs are predicted by taking into account the uncertainty in the trajectory. The contribution of matching an image pair is investigated using information theory principles. Lastly, a different solution to the topology estimation problem is proposed in a bundle adjustment framework. Innovative aspects include the use of fast image similarity criterion combined with a Minimum spanning tree (MST) solution, to obtain a tentative topology. This topology is improved by attempting image matching with the pairs for which there is the most overlap evidence. Unlike previous approaches for large-area mosaicing, our framework is able to deal naturally with cases where time-consecutive images cannot be matched successfully, such as completely unordered sets. Finally, the efficiency of the proposed methods is discussed and a comparison made with other state-of-the-art approaches, using a series of challenging datasets in underwater scenarios

A new approach for the solution of the optimal set-point tracking problem for nonlinear systems

In this paper, a discrete time dynamic integrated system optimisation and parameter estimation algorithm is applied to the solution of the nonlinear tracking optimal control problem. A version of the algorithm with a linear-quadratic model-based problem is developed and implemented in software. The algorithm implemented is tested with simulation examples.

Least square projection: A fast high-precision multidimensional projection technique and its application to document mapping

The problem of projecting multidimensional data into lower dimensions has been pursued by many researchers due to its potential application to data analyses of various kinds. This paper presents a novel multidimensional projection technique based on least square approximations. The approximations compute the coordinates of a set of projected points based on the coordinates of a reduced number of control points with defined geometry. We name the technique Least Square Projections ( LSP). From an initial projection of the control points, LSP defines the positioning of their neighboring points through a numerical solution that aims at preserving a similarity relationship between the points given by a metric in mD. In order to perform the projection, a small number of distance calculations are necessary, and no repositioning of the points is required to obtain a final solution with satisfactory precision. The results show the capability of the technique to form groups of points by degree of similarity in 2D. We illustrate that capability through its application to mapping collections of textual documents from varied sources, a strategic yet difficult application. LSP is faster and more accurate than other existing high-quality methods, particularly where it was mostly tested, that is, for mapping text sets.

A multi-objective adaptive immune algorithm for multi-application NoC mapping

Current SoC design trends are characterized by the integration of larger amount of IPs targeting a wide range of application fields. Such multi-application systems are constrained by a set of requirements. In such scenario network-on-chips (NoC) are becoming more important as the on-chip communication structure. Designing an optimal NoC for satisfying the requirements of each individual application requires the specification of a large set of configuration parameters leading to a wide solution space. It has been shown that IP mapping is one of the most critical parameters in NoC design, strongly influencing the SoC performance. IP mapping has been solved for single application systems using single and multi-objective optimization algorithms. In this paper we propose the use of a multi-objective adaptive immune algorithm (M(2)AIA), an evolutionary approach to solve the multi-application NoC mapping problem. Latency and power consumption were adopted as the target multi-objective functions. To compare the efficiency of our approach, our results are compared with those of the genetic and branch and bound multi-objective mapping algorithms. We tested 11 well-known benchmarks, including random and real applications, and combines up to 8 applications at the same SoC. The experimental results showed that the M(2)AIA decreases in average the power consumption and the latency 27.3 and 42.1 % compared to the branch and bound approach and 29.3 and 36.1 % over the genetic approach.

Probabilistic mapping with mobile robots in structured environments

La mayor parte de los entornos diseñados por el hombre presentan características geométricas específicas. En ellos es frecuente encontrar formas poligonales, rectangulares, circulares . . . con una serie de relaciones típicas entre distintos elementos del entorno. Introducir este tipo de conocimiento en el proceso de construcción de mapas de un robot móvil puede mejorar notablemente la calidad y la precisión de los mapas resultantes. También puede hacerlos más útiles de cara a un razonamiento de más alto nivel. Cuando la construcción de mapas se formula en un marco probabilístico Bayesiano, una especificación completa del problema requiere considerar cierta información a priori sobre el tipo de entorno. El conocimiento previo puede aplicarse de varias maneras, en esta tesis se presentan dos marcos diferentes: uno basado en el uso de primitivas geométricas y otro que emplea un método de representación cercano al espacio de las medidas brutas. Un enfoque basado en características geométricas supone implícitamente imponer un cierto modelo a priori para el entorno. En este sentido, el desarrollo de una solución al problema SLAM mediante la optimización de un grafo de características geométricas constituye un primer paso hacia nuevos métodos de construcción de mapas en entornos estructurados. En el primero de los dos marcos propuestos, el sistema deduce la información a priori a aplicar en cada caso en base a una extensa colección de posibles modelos geométricos genéricos, siguiendo un método de Maximización de la Esperanza para hallar la estructura y el mapa más probables. La representación de la estructura del entorno se basa en un enfoque jerárquico, con diferentes niveles de abstracción para los distintos elementos geométricos que puedan describirlo. Se llevaron a cabo diversos experimentos para mostrar la versatilidad y el buen funcionamiento del método propuesto. En el segundo marco, el usuario puede definir diferentes modelos de estructura para el entorno mediante grupos de restricciones y energías locales entre puntos vecinos de un conjunto de datos del mismo. El grupo de restricciones que se aplica a cada grupo de puntos depende de la topología, que es inferida por el propio sistema. De este modo, se pueden incorporar nuevos modelos genéricos de estructura para el entorno con gran flexibilidad y facilidad. Se realizaron distintos experimentos para demostrar la flexibilidad y los buenos resultados del enfoque propuesto. Abstract Most human designed environments present specific geometrical characteristics. In them, it is easy to find polygonal, rectangular and circular shapes, with a series of typical relations between different elements of the environment. Introducing this kind of knowledge in the mapping process of mobile robots can notably improve the quality and accuracy of the resulting maps. It can also make them more suitable for higher level reasoning applications. When mapping is formulated in a Bayesian probabilistic framework, a complete specification of the problem requires considering a prior for the environment. The prior over the structure of the environment can be applied in several ways; this dissertation presents two different frameworks, one using a feature based approach and another one employing a dense representation close to the measurements space. A feature based approach implicitly imposes a prior for the environment. In this sense, feature based graph SLAM was a first step towards a new mapping solution for structured scenarios. In the first framework, the prior is inferred by the system from a wide collection of feature based priors, following an Expectation-Maximization approach to obtain the most probable structure and the most probable map. The representation of the structure of the environment is based on a hierarchical model with different levels of abstraction for the geometrical elements describing it. Various experiments were conducted to show the versatility and the good performance of the proposed method. In the second framework, different priors can be defined by the user as sets of local constraints and energies for consecutive points in a range scan from a given environment. The set of constraints applied to each group of points depends on the topology, which is inferred by the system. This way, flexible and generic priors can be incorporated very easily. Several tests were carried out to demonstrate the flexibility and the good results of the proposed approach.

Solution of optimal continuous low-thrust transfer using Lie transforms

This paper addresses the problem of optimal constant continuous low-thrust transfer in the context of the restricted two-body problem (R2BP). Using the Pontryagin’s principle, the problem is formulated as a two point boundary value problem (TPBVP) for a Hamiltonian system. Lie transforms obtained through the Deprit method allow us to obtain the canonical mapping of the phase flow as a series in terms of the order of magnitude of the thrust applied. The reachable set of states starting from a given initial condition using optimal control policy is obtained analytically. In addition, a particular optimal transfer can be computed as the solution of a non-linear algebraic equation. Se investiga el uso de series y transformadas de Lie en problemas de optimización de trayectorias de satélites impulsados por motores de bajo empuje