48 resultados para Project-based system


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We present a system for dynamic network resource configuration in environments with bandwidth reservation and path restoration mechanisms. Our focus is on the dynamic bandwidth management results, although the main goal of the system is the integration of the different mechanisms that manage the reserved paths (bandwidth, restoration, and spare capacity planning). The objective is to avoid conflicts between these mechanisms. The system is able to dynamically manage a logical network such as a virtual path network in ATM or a label switch path network in MPLS. This system has been designed to be modular in the sense that in can be activated or deactivated, and it can be applied only in a sub-network. The system design and implementation is based on a multi-agent system (MAS). We also included details of its architecture and implementation

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Consumer reviews, opinions and shared experiences in the use of a product is a powerful source of information about consumer preferences that can be used in recommender systems. Despite the importance and value of such information, there is no comprehensive mechanism that formalizes the opinions selection and retrieval process and the utilization of retrieved opinions due to the difficulty of extracting information from text data. In this paper, a new recommender system that is built on consumer product reviews is proposed. A prioritizing mechanism is developed for the system. The proposed approach is illustrated using the case study of a recommender system for digital cameras

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Final degree project report. It summarizes the email upgrade project that was held at CELLS by Sergio Vicente.

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This paper studies cooperation in a political system dominated by two opportunistic parties competing in a resource-based economy. Since a binding agreement as an external solution might be difficult to enforce due to the close association between the incumbent party and the government, the paper explores the extent to which co-operation between political parties that alternate in office can rely on self-enforcing strategies to provide an internal solution. We show that, for appropriate values of the probability of re-election and the discount factor cooperation in maintaining the value of a state variable is possible, but fragile. Another result is that, in such political framework, debt decisions contain an externality element linked to electoral incentives that creates a bias towards excessive borrowing.

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This work shows the use of adaptation techniques involved in an e-learning system that considers students' learning styles and students' knowledge states. The mentioned e-learning system is built on a multiagent framework designed to examine opportunities to improve the teaching and to motivate the students to learn what they want in a user-friendly and assisted environment

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Report for the scientific sojourn carried out at the Paul Drude Institut für Festkörperelektronik of the Stanford University, USA, from 2010 to 2012. The objective of this project is the transport and control of electronic charge and spin along GaAs-based semiconductor heterostructures. The electronic transport has been achieved by taking advantage of the piezolectric field induced by surface acoustic waves in non-centrosymmetric materials like GaAs. This piezolectric field separates photogenerated electrons and holes at different positions along the acoustic wave, where they acummulate and are transported at the same velocity as the wave. Two different kinds of structures have been studied: quantum wells grown along the (110) direction, both intrinsic and n-doped, as well as GaAs nanowires. The analysis of the charge acoustic transport was performed by micro-photoluminescence, whereas the detection of the spin transport was done either by analyzing the polarization state of the emitted photoluminescence or by Kerr reflectometry. Our results in GaAs quantum wells show that charge and spin transport is clearly observed at the non-doped structures,obtaining spin lifetimes of the order of several nanoseconds, whereas no acoutically induced spin transport was detected for the n-doped quantum wells. In the GaAs nanowires, we were able of transporting successfully both electrons and holes along the nanowire axis, but no conservation of the spin polarization has been observed until now. The photoluminescence emitted by these structures after acoustic transport, however, shows anti-bunching characteristics, making this system a very good candidate for its use as single photon emitters.

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Earth System Models (ESM) have been successfuly developed over past few years, and are currently beeing used for simulating present day-climate, seasonal to interanual predictions of climate change. The supercomputer performance plays an important role in climate modeling since one of the challenging issues for climate modellers is to efficiently and accurately couple earth System components on present day computers architectures. At the Barcelona Supercomputing Center (BSC), we work with the EC- Earth System Model. The EC- Earth is an ESM, which currently consists of an atmosphere (IFS) and an ocean (NEMO) model that communicate with each other through the OASIS coupler. Additional modules (e.g. for chemistry and vegetation ) are under development. The EC-Earth ESM has been ported successfully over diferent high performance computin platforms (e.g, IBM P6 AIX, CRAY XT-5, Intelbased Linux Clusters, SGI Altix) at diferent sites in Europ (e.g., KNMI, ICHEC, ECMWF). The objective of the first phase of the project was to identify and document the issues related with the portability and performance of EC-Earth on the MareNostrum supercomputer, a System based on IBM PowerPC 970MP processors and run under a Linux Suse Distribution. EC-Earth was successfully ported to MareNostrum, and a compilation incompatibilty was solved by a two step compilation approach using XLF version 10.1 and 12.1 compilers. In addition, the EC-Earth performance was analyzed with respect to escalability and trace analysis with the Paravear software. This analysis showed that EC-Earth with a larger number of IFS CPUs (<128) is not feasible at the moment since some issues exists with the IFS-NEMO balance and MPI Communications.

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The emergence of the Web 2.0 technologies in the last years havechanged the way people interact with knowledge. Services for cooperation andcollaboration have placed the user in the centre of a new knowledge buildingspace. The development of new second generation learning environments canbenefit from the potential of these Web 2.0 services when applied to aneducational context. We propose a methodology for designing learningenvironments that relates Web 2.0 services with the functional requirements ofthese environments. In particular, we concentrate on the design of the KRSMsystem to discuss the components of this methodology and its application.

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Student guidance is an always desired characteristic in any educational system, butit represents special difficulty if it has to be deployed in an automated way to fulfilsuch needs in a computer supported educational tool. In this paper we explorepossible avenues relying on machine learning techniques, to be included in a nearfuture -in the form of a tutoring navigational tool- in a teleeducation platform -InterMediActor- currently under development. Since no data from that platform isavailable yet, the preliminary experiments presented in this paper are builtinterpreting every subject in the Telecommunications Degree at Universidad CarlosIII de Madrid as an aggregated macro-competence (following the methodologicalconsiderations in InterMediActor), such that marks achieved by students can beused as data for the models, to be replaced in a near future by real data directlymeasured inside InterMediActor. We evaluate the predictability of students qualifications, and we deploy a preventive early detection system -failure alert-, toidentify those students more prone to fail a certain subject such that correctivemeans can be deployed with sufficient anticipation.

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This final year project presents the design principles and prototype implementation of BIMS (Biomedical Information Management System), a flexible software system which provides an infrastructure to manage all information required by biomedical research projects.The BIMS project was initiated with the motivation to solve several limitations in medical data acquisition of some research projects, in which Universitat Pompeu Fabra takes part. These limitations,based on the lack of control mechanisms to constraint information submitted by clinicians, impact on the data quality, decreasing it.BIMS can easily be adapted to manage information of a wide variety of clinical studies, not being limited to a given clinical specialty. The software can manage both, textual information, like clinical data (measurements, demographics, diagnostics, etc ...), as well as several kinds of medical images (magnetic resonance imaging, computed tomography, etc ...). Moreover, BIMS provides a web - based graphical user interface and is designed to be deployed in a distributed andmultiuser environment. It is built on top of open source software products and frameworks.Specifically, BIMS has been used to represent all clinical data being currently used within the CardioLab platform (an ongoing project managed by Universitat Pompeu Fabra), demonstratingthat it is a solid software system, which could fulfill requirements of a real production environment.

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The public transportation is gaining importance every year basically duethe population growth, environmental policies and, route and streetcongestion. Too able an efficient management of all the resources relatedto public transportation, several techniques from different areas are beingapplied and several projects in Transportation Planning Systems, indifferent countries, are being developed. In this work, we present theGIST Planning Transportation Systems, a Portuguese project involving twouniversities and six public transportation companies. We describe indetail one of the most relevant modules of this project, the crew-scheduling module. The crew-scheduling module is based on the application of meta-heuristics, in particular GRASP, tabu search and geneticalgorithm to solve the bus-driver-scheduling problem. The metaheuristicshave been successfully incorporated in the GIST Planning TransportationSystems and are actually used by several companies.

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Background: Network reconstructions at the cell level are a major development in Systems Biology. However, we are far from fully exploiting its potentialities. Often, the incremental complexity of the pursued systems overrides experimental capabilities, or increasingly sophisticated protocols are underutilized to merely refine confidence levels of already established interactions. For metabolic networks, the currently employed confidence scoring system rates reactions discretely according to nested categories of experimental evidence or model-based likelihood. Results: Here, we propose a complementary network-based scoring system that exploits the statistical regularities of a metabolic network as a bipartite graph. As an illustration, we apply it to the metabolism of Escherichia coli. The model is adjusted to the observations to derive connection probabilities between individual metabolite-reaction pairs and, after validation, to assess the reliability of each reaction in probabilistic terms. This network-based scoring system uncovers very specific reactions that could be functionally or evolutionary important, identifies prominent experimental targets, and enables further confirmation of modeling results. Conclusions: We foresee a wide range of potential applications at different sub-cellular or supra-cellular levels of biological interactions given the natural bipartivity of many biological networks.

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In this work we explore the multivariate empirical mode decomposition combined with a Neural Network classifier as technique for face recognition tasks. Images are simultaneously decomposed by means of EMD and then the distance between the modes of the image and the modes of the representative image of each class is calculated using three different distance measures. Then, a neural network is trained using 10- fold cross validation in order to derive a classifier. Preliminary results (over 98 % of classification rate) are satisfactory and will justify a deep investigation on how to apply mEMD for face recognition.