Disseny i implementació de la base de dades d'un sistema de recollida de dades d'activitat física provinents de dispositius wearables, en el marc d'un projecte big data de salut

Aquest treball de final de carrera vol donar una solució a un suposat encàrrec de la Unió Europea de construir una base de dades relacional que permeti emmagatzemar dades de l'activitat física dels ciutadans, obtingudes a partir de dispositius wearables, i dades de l'estat de salut i malalties diagnosticades, recollides pels sistemes informàtics dels diferents serveis de salut. Amb totes aquestes dades recopilades la nostra base de dades permetrà, a través d'aplicacions d'alt nivell, extreure informació útil que permeti conèixer l'estat de salut real dels ciutadans i dissenyar actuacions i campanyes que permetin la seva millora.

LHC luminosity measurement with the ATLAS-MPX detectors

En opération depuis 2008, l’expérience ATLAS est la plus grande de toutes les expériences au LHC. Les détecteurs ATLAS- MPX (MPX) installés dans ATLAS sont basés sur le détecteur au silicium à pixels Medipix2 qui a été développé par la collaboration Medipix au CERN pour faire de l’imagerie en temps réel. Les détecteurs MPX peuvent être utilisés pour mesurer la luminosité. Ils ont été installés à seize différents endroits dans les zones expérimentale et technique d’ATLAS en 2008. Le réseau MPX a recueilli avec succès des données indépendamment de la chaîne d’enregistrement des données ATLAS de 2008 à 2013. Chaque détecteur MPX fournit des mesures de la luminosité intégrée du LHC. Ce mémoire décrit la méthode d’étalonnage de la luminosité absolue mesurée avec les détectors MPX et la performance des détecteurs MPX pour les données de luminosité en 2012. Une constante d’étalonnage de la luminosité a été déterminée. L’étalonnage est basé sur technique de van der Meer (vdM). Cette technique permet la mesure de la taille des deux faisceaux en recouvrement dans le plan vertical et horizontal au point d’interaction d’ATLAS (IP1). La détermination de la luminosité absolue nécessite la connaissance précise de l’intensité des faisceaux et du nombre de trains de particules. Les trois balayages d’étalonnage ont été analysés et les résultats obtenus par les détecteurs MPX ont été comparés aux autres détecteurs d’ATLAS dédiés spécifiquement à la mesure de la luminosité. La luminosité obtenue à partir des balayages vdM a été comparée à la luminosité des collisions proton- proton avant et après les balayages vdM. Le réseau des détecteurs MPX donne des informations fiables pour la détermination de la luminosité de l’expérience ATLAS sur un large intervalle (luminosité de 5 × 10^29 cm−2 s−1 jusqu’à 7 × 10^33 cm−2 s−1 .

“Reconstruction of Gene Regulatory Network from Expression Profile of Plasma RNA Data of Colorectal Cancer Patients using Soft Computing Techniques”

Microarray data analysis is one of data mining tool which is used to extract meaningful information hidden in biological data. One of the major focuses on microarray data analysis is the reconstruction of gene regulatory network that may be used to provide a broader understanding on the functioning of complex cellular systems. Since cancer is a genetic disease arising from the abnormal gene function, the identification of cancerous genes and the regulatory pathways they control will provide a better platform for understanding the tumor formation and development. The major focus of this thesis is to understand the regulation of genes responsible for the development of cancer, particularly colorectal cancer by analyzing the microarray expression data. In this thesis, four computational algorithms namely fuzzy logic algorithm, modified genetic algorithm, dynamic neural fuzzy network and Takagi Sugeno Kang-type recurrent neural fuzzy network are used to extract cancer specific gene regulatory network from plasma RNA dataset of colorectal cancer patients. Plasma RNA is highly attractive for cancer analysis since it requires a collection of small amount of blood and it can be obtained at any time in repetitive fashion allowing the analysis of disease progression and treatment response.

Social Computing Data Repository

Social Computing Data Repository hosts data from a collection of many different social media sites, most of which have blogging capacity. Some of the prominent social media sites included in this repository are BlogCatalog, Twitter, MyBlogLog, Digg, StumbleUpon, del.icio.us, MySpace, LiveJournal, The Unofficial Apple Weblog (TUAW), Reddit, etc. The repository contains various facets of blog data including blog site metadata like, user defined tags, predefined categories, blog site description; blog post level metadata like, user defined tags, date and time of posting; blog posts; blog post mood (which is defined as the blogger's emotions when (s)he wrote the blog post); blogger name; blog post comments; and blogger social network.

An Animating Spark: Mundane Computing and the Web of Data

Network connectivity is reaching more and more into the physical world. This is potentially transformative – allowing every object and service in the world to talk to one other—and to their users—through any networked interface; where online services are the connective tissue of the physical world and where physical objects are avatars of online services.

Sistema de protección de Habeas Data

El desarrollo que está presentando el tema, hace que la información al respecto resulte algo limitada, no es mucha la literatura que hasta el momento se haya producido, especialmente en países donde la vida del Habeas Data es más corta. Por ello es que nuestra investigación resulta una herramienta

Conflicto por el agua: un análisis geopolítico al sistema Tigris-Éufrates. 1990-2003

El interés de este estudio de caso es analizar la situación vivida entre los Estados de la cuenca del Sistema Tigris-Éufrates, un recurso hídrico transfronterizo entre 1990 y el 2003. Se estudia y explica cómo el Interés Nacional de Turquía, Siria e Irak, Estados ribereños del Sistema supuso un obstáculo para la implementación de la Gestión Integrada de Recursos Hídricos sobre la cuenca, al impedir la cooperación y coordinación de las políticas gubernamentales, dificultando la protección de la cuenca y la garantía del acceso al recurso de forma equitativa. Este trabajo se enmarca en los estudios sobre Seguridad Ambiental, particularmente en la teoría de la Escasez Ambiental de Thomas Homer-Dixon y el Grupo de Toronto, referente a la relación entre la escasez de un recurso natural renovable y el surgimiento de un conflicto.

Diseño de un sistema de gestión basado en procesos. Caso: empresa dedicada a la importación y venta de equipos para Data Centers

El presente proyecto es el desarrollo de una herramienta de gestión basada en procesos para la empresa KEOPSPOWER CIA. LTDA., empresa dedicada a la importación y comercialización de equipos para Centros de Cómputo. Con base en la teoría de gestión por procesos, se presenta una propuesta de un sistema de gestión que considera las dimensiones de recurso humano, sistemas de información y procesos, como componentes de la gestión empresarial, desde la razón de ser de la organización. El presente trabajo está conformado por un primer capítulo teórico que recopila los conceptos más relevantes y en los cuales se apoya el desarrollo del sistema de gestión, posteriormente se analiza la situación actual de la organización en función de las fuerzas competitivas y tomando en cuenta la dirección estratégica, para en un tercer capítulo realizar la propuesta del sistema de gestión. En el capítulo tres se presenta la propuesta propiamente dicha, considerando las dimensiones de la gestión, es así que se realiza el levantamiento de procesos a partir de la cadena de valor de la organización, se definen indicadores de gestión, y se realiza la propuesta para la mejora de las dimensiones de Recurso Humano, y Sistemas de Información de KEOPSPOWER CIA. LTDA. Finalmente dentro de este capítulo se realiza la proyección del ingreso, con el fin de comprobar la hipótesis planteada, que sostiene que, la implementación de un Sistema de Gestión basado en Procesos mejora la rentabilidad organizacional. La principal herramienta de consulta ha sido la observación directa, así como las entrevistas con los diferentes niveles funcionales de la organización, así como documentación referente al plan estratégico de la organización.

Tripleclouds: an efficient method for representing horizontal cloud inhomogeneity in 1D radiation schemes by using three regions at each height

Radiation schemes in general circulation models currently make a number of simplifications when accounting for clouds, one of the most important being the removal of horizontal inhomogeneity. A new scheme is presented that attempts to account for the neglected inhomogeneity by using two regions of cloud in each vertical level of the model as opposed to one. One of these regions is used to represent the optically thinner cloud in the level, and the other represents the optically thicker cloud. So, along with the clear-sky region, the scheme has three regions in each model level and is referred to as “Tripleclouds.” In addition, the scheme has the capability to represent arbitrary vertical overlap between the three regions in pairs of adjacent levels. This scheme is implemented in the Edwards–Slingo radiation code and tested on 250 h of data from 12 different days. The data are derived from cloud retrievals using radar, lidar, and a microwave radiometer at Chilbolton, southern United Kingdom. When the data are grouped into periods equivalent in size to general circulation model grid boxes, the shortwave plane-parallel albedo bias is found to be 8%, while the corresponding bias is found to be less than 1% using Tripleclouds. Similar results are found for the longwave biases. Tripleclouds is then compared to a more conventional method of accounting for inhomogeneity that multiplies optical depths by a constant scaling factor, and Tripleclouds is seen to improve on this method both in terms of top-of-atmosphere radiative flux biases and internal heating rates.

Running Climate Models On The NERC Cluster Grid Using G-Rex

Compute grids are used widely in many areas of environmental science, but there has been limited uptake of grid computing by the climate modelling community, partly because the characteristics of many climate models make them difficult to use with popular grid middleware systems. In particular, climate models usually produce large volumes of output data, and running them usually involves complicated workflows implemented as shell scripts. For example, NEMO (Smith et al. 2008) is a state-of-the-art ocean model that is used currently for operational ocean forecasting in France, and will soon be used in the UK for both ocean forecasting and climate modelling. On a typical modern cluster, a particular one year global ocean simulation at 1-degree resolution takes about three hours when running on 40 processors, and produces roughly 20 GB of output as 50000 separate files. 50-year simulations are common, during which the model is resubmitted as a new job after each year. Running NEMO relies on a set of complicated shell scripts and command utilities for data pre-processing and post-processing prior to job resubmission. Grid Remote Execution (G-Rex) is a pure Java grid middleware system that allows scientific applications to be deployed as Web services on remote computer systems, and then launched and controlled as if they are running on the user's own computer. Although G-Rex is general purpose middleware it has two key features that make it particularly suitable for remote execution of climate models: (1) Output from the model is transferred back to the user while the run is in progress to prevent it from accumulating on the remote system and to allow the user to monitor the model; (2) The client component is a command-line program that can easily be incorporated into existing model work-flow scripts. G-Rex has a REST (Fielding, 2000) architectural style, which allows client programs to be very simple and lightweight and allows users to interact with model runs using only a basic HTTP client (such as a Web browser or the curl utility) if they wish. This design also allows for new client interfaces to be developed in other programming languages with relatively little effort. The G-Rex server is a standard Web application that runs inside a servlet container such as Apache Tomcat and is therefore easy to install and maintain by system administrators. G-Rex is employed as the middleware for the NERC1 Cluster Grid, a small grid of HPC2 clusters belonging to collaborating NERC research institutes. Currently the NEMO (Smith et al. 2008) and POLCOMS (Holt et al, 2008) ocean models are installed, and there are plans to install the Hadley Centre’s HadCM3 model for use in the decadal climate prediction project GCEP (Haines et al., 2008). The science projects involving NEMO on the Grid have a particular focus on data assimilation (Smith et al. 2008), a technique that involves constraining model simulations with observations. The POLCOMS model will play an important part in the GCOMS project (Holt et al, 2008), which aims to simulate the world’s coastal oceans. A typical use of G-Rex by a scientist to run a climate model on the NERC Cluster Grid proceeds as follows :(1) The scientist prepares input files on his or her local machine. (2) Using information provided by the Grid’s Ganglia3 monitoring system, the scientist selects an appropriate compute resource. (3) The scientist runs the relevant workflow script on his or her local machine. This is unmodified except that calls to run the model (e.g. with “mpirun”) are simply replaced with calls to "GRexRun" (4) The G-Rex middleware automatically handles the uploading of input files to the remote resource, and the downloading of output files back to the user, including their deletion from the remote system, during the run. (5) The scientist monitors the output files, using familiar analysis and visualization tools on his or her own local machine. G-Rex is well suited to climate modelling because it addresses many of the middleware usability issues that have led to limited uptake of grid computing by climate scientists. It is a lightweight, low-impact and easy-to-install solution that is currently designed for use in relatively small grids such as the NERC Cluster Grid. A current topic of research is the use of G-Rex as an easy-to-use front-end to larger-scale Grid resources such as the UK National Grid service.

Evaluation of a large-eddy model simulation of a mixed-phase altocumulus cloud using microwave radiometer, lidar and Doppler radar data

Using the Met Office large-eddy model (LEM) we simulate a mixed-phase altocumulus cloud that was observed from Chilbolton in southern England by a 94 GHz Doppler radar, a 905 nm lidar, a dual-wavelength microwave radiometer and also by four radiosondes. It is important to test and evaluate such simulations with observations, since there are significant differences between results from different cloud-resolving models for ice clouds. Simulating the Doppler radar and lidar data within the LEM allows us to compare observed and modelled quantities directly, and allows us to explore the relationships between observed and unobserved variables. For general-circulation models, which currently tend to give poor representations of mixed-phase clouds, the case shows the importance of using: (i) separate prognostic ice and liquid water, (ii) a vertical resolution that captures the thin layers of liquid water, and (iii) an accurate representation the subgrid vertical velocities that allow liquid water to form. It is shown that large-scale ascents and descents are significant for this case, and so the horizontally averaged LEM profiles are relaxed towards observed profiles to account for these. The LEM simulation then gives a reasonable. cloud, with an ice-water path approximately two thirds of that observed, with liquid water at the cloud top, as observed. However, the liquid-water cells that form in the updraughts at cloud top in the LEM have liquid-water paths (LWPs) up to half those observed, and there are too few cells, giving a mean LWP five to ten times smaller than observed. In reality, ice nucleation and fallout may deplete ice-nuclei concentrations at the cloud top, allowing more liquid water to form there, but this process is not represented in the model. Decreasing the heterogeneous nucleation rate in the LEM increased the LWP, which supports this hypothesis. The LEM captures the increase in the standard deviation in Doppler velocities (and so vertical winds) with height, but values are 1.5 to 4 times smaller than observed (although values are larger in an unforced model run, this only increases the modelled LWP by a factor of approximately two). The LEM data show that, for values larger than approximately 12 cm s(-1), the standard deviation in Doppler velocities provides an almost unbiased estimate of the standard deviation in vertical winds, but provides an overestimate for smaller values. Time-smoothing the observed Doppler velocities and modelled mass-squared-weighted fallspeeds shows that observed fallspeeds are approximately two-thirds of the modelled values. Decreasing the modelled fallspeeds to those observed increases the modelled IWC, giving an IWP 1.6 times that observed.

Results from the CERN pilot CLOUD experiment

During a 4-week run in October–November 2006, a pilot experiment was performed at the CERN Proton Synchrotron in preparation for the Cosmics Leaving OUtdoor Droplets (CLOUD) experiment, whose aim is to study the possible influence of cosmic rays on clouds. The purpose of the pilot experiment was firstly to carry out exploratory measurements of the effect of ionising particle radiation on aerosol formation from trace H2SO4 vapour and secondly to provide technical input for the CLOUD design. A total of 44 nucleation bursts were produced and recorded, with formation rates of particles above the 3 nm detection threshold of between 0.1 and 100 cm−3 s−1, and growth rates between 2 and 37 nm h−1. The corresponding H2SO4 concentrations were typically around 106 cm−3 or less. The experimentally-measured formation rates and H2SO4 concentrations are comparable to those found in the atmosphere, supporting the idea that sulphuric acid is involved in the nucleation of atmospheric aerosols. However, sulphuric acid alone is not able to explain the observed rapid growth rates, which suggests the presence of additional trace vapours in the aerosol chamber, whose identity is unknown. By analysing the charged fraction, a few of the aerosol bursts appear to have a contribution from ion-induced nucleation and ion-ion recombination to form neutral clusters. Some indications were also found for the accelerator beam timing and intensity to influence the aerosol particle formation rate at the highest experimental SO2 concentrations of 6 ppb, although none was found at lower concentrations. Overall, the exploratory measurements provide suggestive evidence for ion-induced nucleation or ion-ion recombination as sources of aerosol particles. However in order to quantify the conditions under which ion processes become significant, improvements are needed in controlling the experimental variables and in the reproducibility of the experiments. Finally, concerning technical aspects, the most important lessons for the CLOUD design include the stringent requirement of internal cleanliness of the aerosol chamber, as well as maintenance of extremely stable temperatures (variations below 0.1 _C).