GMODI : Gestión y mantenimiento Online de departamentos informáticos

La finalitat d'aquest projecte és la d'aconseguir d'una banda la gestió de recanvis per als equips informàtics de l'empresa tals com, tonners d'impressores làser i faxos, cartutxos de tinta, escàners i terminals de fàbrica i finalment impressores d'impressió tèrmica per a etiquetes dels productes de la nostra fàbrica. Per l'altre costat tindrem el manteniment dels equips informàtics de l'empresa, és dir els PC's de feina.

Estudi comparatiu de la gestió de memòria de dues màquines virtuals

En aquest projecte s'han comparat els gestors de memòria de les màquines virtuals de Java i del projecte Mono.

Coevolution of adaptive technology, maladaptive culture and population size in a producer-scrounger game.

Technology (i.e. tools, methods of cultivation and domestication, systems of construction and appropriation, machines) has increased the vital rates of humans, and is one of the defining features of the transition from Malthusian ecological stagnation to a potentially perpetual rising population growth. Maladaptations, on the other hand, encompass behaviours, customs and practices that decrease the vital rates of individuals. Technology and maladaptations are part of the total stock of culture carried by the individuals in a population. Here, we develop a quantitative model for the coevolution of cumulative adaptive technology and maladaptive culture in a 'producer-scrounger' game, which can also usefully be interpreted as an 'individual-social' learner interaction. Producers (individual learners) are assumed to invent new adaptations and maladaptations by trial-and-error learning, insight or deduction, and they pay the cost of innovation. Scroungers (social learners) are assumed to copy or imitate (cultural transmission) both the adaptations and maladaptations generated by producers. We show that the coevolutionary dynamics of producers and scroungers in the presence of cultural transmission can have a variety of effects on population carrying capacity. From stable polymorphism, where scroungers bring an advantage to the population (increase in carrying capacity), to periodic cycling, where scroungers decrease carrying capacity, we find that selection-driven cultural innovation and transmission may send a population on the path of indefinite growth or to extinction.

Ontologías Turísticas Geográficas : creación de una ontología sobre rutas turísticas (a Pie o en Bicicleta) por espacios naturales

El turismo es un área en constante crecimiento en la cual, la aparición de las nuevas tecnologías y, fundamentalmente, de Internet, ha tenido un gran impacto en los procedimientos internos de los agentes turísticos y en los métodos de contratación y de búsqueda de información por parte de los usuarios. Por otro lado, la cantidad ingente de información disponible en Internet y el gran desorden existente, provoca la aparición del concepto de Web semántica, una tecnología que dota a las máquinas de un nivel de compresión de la Web suficiente como para hacer de la búsqueda y el acceso a la información una tarea sencilla y natural. Este artículo trata, en primer lugar, de analizar el estado del arte de la Web semántica relacionada con el ámbito del turismo, presentando las ontologías turísticas disponibles en la actualidad para, a continuación, describir el desarrollo de una ontología específica dentro del dominio de las rutas turísticas. Con esta ontología, a través de un ejemplo, se trata de demostrar la utilidad de esta tecnología a la hora de catalogar información relacionada, disponible y dispersa por páginas Web en Internet.

Monitorización de la temperatura de un CPD mediante una red de sensores inalámbricos

Con este proyecto se pretende que una organización sea más consciente del estado de sus máquinas y anticiparse a una situación de pérdida de información, parada de servicios o parada por sobrecalentamiento de servidores.

Mejora diagnóstica de hepatopatías de afectación difusa mediante técnicas de inteligencia artificial

The automatic diagnostic discrimination is an application of artificial intelligence techniques that can solve clinical cases based on imaging. Diffuse liver diseases are diseases of wide prominence in the population and insidious course, yet early in its progression. Early and effective diagnosis is necessary because many of these diseases progress to cirrhosis and liver cancer. The usual technique of choice for accurate diagnosis is liver biopsy, an invasive and not without incompatibilities one. It is proposed in this project an alternative non-invasive and free of contraindications method based on liver ultrasonography. The images are digitized and then analyzed using statistical techniques and analysis of texture. The results are validated from the pathology report. Finally, we apply artificial intelligence techniques as Fuzzy k-Means or Support Vector Machines and compare its significance to the analysis Statistics and the report of the clinician. The results show that this technique is significantly valid and a promising alternative as a noninvasive diagnostic chronic liver disease from diffuse involvement. Artificial Intelligence classifying techniques significantly improve the diagnosing discrimination compared to other statistics.

GNU/Linux - Desenvolupaments intel·ligents : migració de sistemes Windows a Linux

L'empresa Desenvolupaments Intel·ligents es dedica a la creació del software financer i borsari. Tot el sistema informàtic esta basat en màquines amb plataformes Microsoft Windows. S'ha decidit implementar un nou sistema informàtic basat en GNU/Linux. Aquest és l'objecte d'aquest treball. El nou sistema informàtic basat en GNU/Linux ha de incloure tots els equips clients (que seran els ordinadors nous) i els servidors (es reaprofitaran els ordinadors antics) cobrint tots els serveis que abans donava el servidors antics mitjançant aquest sistema operatiu i software lliure.

Desarrollo de aplicaciones en entornos de software libre

El projecte té com idea fonamental crear un programari que permeti la instal·lació de paquets per mitjà de la xarxa en diverses màquines que es trobin registrades en la Base de dades, i a la vegada, es tenen dos mòduls un per a l'aplicació servidor i altre per a l'aplicació client.

Disseny i implantació de l'estructura informàtica de DaVinci School

Creació d'una infraestructura informàtica d'un centre educatiu, amb xarxes separades per a aules, secretaria i seminaris. Serveis centralitzats en un servidor amb màquines virtuals.

Refrigeració de les gillettes d’ una talladora industrial

L’empresa Proslit Equipment forma part del Grup Comexi i la seva activitat consisteix en la fabricació de màquines talladores de material flexible. Degut als avenços tecnològics, s’han incrementat les prestacions de les seves màquines, entre altres coses, s’ha augmentat la velocitat de tall del film fins a 800 m/min. Aquest factor afegit a condicionants com per exemple treballar amb materials gruixuts i abrasius, a temperatures ambientals elevades, etc. fa que sorgeixi una problemàtica en el tall gillette. Degut a la fricció entre el film que circula i les gillettes que el tallen, es crea una energia calorífica que fa augmentar la temperatura de les gillettes fins a tal extrem que aquestes provoquen petites fusions del plàstic, aquest s’incrusta a les gillettes que s’acaben trencant. L’objecte principal d’aquest projecte és fer una anàlisi tècnica mitjançant elements finits de la problemàtica que s’ha detectat a les màquines talladores de l’empresa Proslit Equipment, concretament de l’escalfament de les gillettes utilitzades en el sistema de tall. Es pretén crear un model teòric que s’aproximi al màxim a la realitat de manera que es pugui observar el comportament tèrmic del sistema de tall en funció de les condicions que es determinin com a més desfavorables. Una vegada s’obtinguin aquests resultats teòrics, es valoraran i es proposaran solucions

Solucions per a la virtualització de servidors

Projecte sobre la comparativa de cinc solucions de virtualització centrant-nos especialment en el rendiment de les màquines virtualitzades, extraient informació d'aquestes mitjançant la utilització de benchmarks i posterior anàlisi de les dades obtingudes.

Viri, Remote execution of Python scripts

Viri is a system for automatic distribution and execution of Python code on remote machines. This is especially useful when dealing with a large group of hosts.With Viri, Sysadmins can write their own scripts, and easily distribute and execute them on any number of remote machines. Depending on the number of computers to administrate, Viri can save thousands of hours, that Sysadmins would spend transferring files, logging into remote hosts, and waiting for the scripts to finish. Viri automates the whole process.Viri can also be useful for remotely managing host settings. It should work together with an application where the information about hosts would be maintained. This information can include cron tasks, firewall rules, backup settings,... After a simple Integration of this application with your Viri infrastructure, you can change any settings in the application, and see how it gets applied on the target host automatically.

Effective diagnosis of Alzheimer's disease by means of large margin-based methodology.

BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

Identification of pharmaceutical tablets by Raman spectroscopy and chemometrics

Raman spectroscopy has become an attractive tool for the analysis of pharmaceutical solid dosage forms. In the present study it is used to ensure the identity of tablets. The two main applications of this method are release of final products in quality control and detection of counterfeits. Twenty-five product families of tablets have been included in the spectral library and a non-linear classification method, the Support Vector Machines (SVMs), has been employed. Two calibrations have been developed in cascade: the first one identifies the product family while the second one specifies the formulation. A product family comprises different formulations that have the same active pharmaceutical ingredient (API) but in a different amount. Once the tablets have been classified by the SVM model, API peaks detection and correlation are applied in order to have a specific method for the identification and allow in the future to discriminate counterfeits from genuine products. This calibration strategy enables the identification of 25 product families without error and in the absence of prior information about the sample. Raman spectroscopy coupled with chemometrics is therefore a fast and accurate tool for the identification of pharmaceutical tablets.

Decision fusion for the classification of hyperspectral data: Outcome of the 2008 GRS-S data fusion contest

The 2008 Data Fusion Contest organized by the IEEE Geoscience and Remote Sensing Data Fusion Technical Committee deals with the classification of high-resolution hyperspectral data from an urban area. Unlike in the previous issues of the contest, the goal was not only to identify the best algorithm but also to provide a collaborative effort: The decision fusion of the best individual algorithms was aiming at further improving the classification performances, and the best algorithms were ranked according to their relative contribution to the decision fusion. This paper presents the five awarded algorithms and the conclusions of the contest, stressing the importance of decision fusion, dimension reduction, and supervised classification methods, such as neural networks and support vector machines.