Creation of a carrier-grade telco based on a voice over IP backbone

En aquesta memòria l'autor, fent servir un enfoc modern, redissenya i implementa la plataforma que una empresa de telecomunicacions del segle 21 necessita per poder donar serveis de telefonia i comunicacions als seus usuaris i clients. Al llarg d'aquesta exposició es condueix al lector des d'una fase inicial de disseny fins a la implementació i posada en producció del sistema final desenvolupat, centrant-nos en solucionar les necessitats actuals que això implica. Aquesta memòria cubreix el software, hardware i els processos de negoci associats al repte de fer realitat aquest objectiu, i presenta al lector les múltiples tecnologies emprades per aconseguir-ho, fent emfàsi en la convergència actual de xarxes cap al concepte de xarxes IP i basant-se en aquesta tendència i utilitzant aquesta tecnologia de veu sobre IP per donar forma a la plataforma que finalment, de forma pràctica, es posa en producció.

The Role of supply constraints in multiplier analysis

Multiplier analysis based upon the information contained in Leontief's inverse is undoubtedly part of the core of the input-output methodology and numerous applications an extensions have been developed that exploit its informational content. Nonetheless there are some implicit theoretical assumptions whose implications have perhaps not been fully assessed. This is the case of the 'excess capacity' assumption. Because of this assumption resources are available as needed to adjust production to new equilibrium states. In real world applications, however, new resources are scarce and costly. Supply constraints kick in and hence resource allocation needs to take them into account to really assess the effect of government policies. Using a closed general equilibrium model that incorporates supply constraints, we perform some simple numerical exercises and proceed to derive a 'constrained' multiplier matrix that can be compared with the standard 'unrestricted' multiplier matrix. Results show that the effectiveness of expenditure policies hinges critically on whether or not supply constraints are considered.

Creació d'un entorn web de treball per a una biblioteca : Fent ús de Struts, Tiles i Hibernate

El següent projecte final de carrera vol assolir assolir la creació d'un entorn web de treball per a una Biblioteca. L'aplicació al món real es base en un mòdul administratiu, que podrà ser utilitzat pels treballadors de la pròpia Biblioteca i un mòdul que servirà de consulta als socis.

Bases de dades multimedia

La part del treball de recerca inclou un estudi que recull l'evolució de les bases de dades des del seu començament fins a l'actualitat, incloent-hi una previsió del futur de les bases de dades; finalment, com a aprofundiment, s'hi estudien les bases de dades multimèdia. D'altra banda, la part pràctica mira d'aplicar tots el coneixements adquirits durant l'estudi de recerca i durant les diferents assignatures de la carrera, i intenta obtenir una aplicació que es pugui fer servir en el món real.

Electoral competition through issue selection

Politics must tackle multiple issues at once. In a first-best world, political competition constrains parties to prioritize issues according to the voters' true concerns. In the real world, the opposite also happens: parties manipulate voter priorities by emphasizing issues selectively during the political campaign. This phenomenon, known as priming, should allow parties to pay less attention to the issues that they intend to mute. We develop a model of endogenous issue ownership in which two vote-seeking parties (i) invest to attract voters with "better" policy proposals and (ii) choose a communication campaign to focus voter attention on specific issues. We identify novel feedbacks between communication and investment. In particular, we find that stronger priming effects can backfire by constraining parties to invest more resources in all issues, including the ones they would otherwise intend to mute. We also identify under which conditions parties prefer to focus on their "historical issues" or to engage in issue stealing. Typically, the latter happens when priming effects are strong, and historical reputations differentiates parties less.

Embedding Emotional Context in Recommender Systems

Emotions are crucial for user's decision making in recommendation processes. We first introduce ambient recommender systems, which arise from the analysis of new trends on the exploitation of the emotional context in the next generation of recommender systems. We then explain some results of these new trends in real-world applications through the smart prediction assistant (SPA) platform in an intelligent learning guide with more than three million users. While most approaches to recommending have focused on algorithm performance. SPA makes recommendations to users on the basis of emotional information acquired in an incremental way. This article provides a cross-disciplinary perspective to achieve this goal in such recommender systems through a SPA platform. The methodology applied in SPA is the result of a bunch of technology transfer projects for large real-world rccommender systems

Agenda d'actes i gestió fotogràfica web

L'objectiu principal d'aquest projecte ha estat aprofundir en la construcció de programari, abordant totes les etapes d'un projecte de construcció de programari des de la perspectiva de l'enginyeria del software (anàlisi, disseny, implementació i proves) i utilitzant el paradigma de programació Orientada a l'Objecte mitjançant l'ús de la tecnologia J2EE, conjuntament amb bastions de programari de gran importància en el mon real i per tant, en l'àmbit de desenvolupament de programari i tecnològic actuals.

Predictability of music descriptor time series and its application to cover song detection

Intuitively, music has both predictable and unpredictable components. In this work we assess this qualitative statement in a quantitative way using common time series models fitted to state-of-the-art music descriptors. These descriptors cover different musical facets and are extracted from a large collection of real audio recordings comprising a variety of musical genres. Our findings show that music descriptor time series exhibit a certain predictability not only for short time intervals, but also for mid-term and relatively long intervals. This fact is observed independently of the descriptor, musical facet and time series model we consider. Moreover, we show that our findings are not only of theoretical relevance but can also have practical impact. To this end we demonstrate that music predictability at relatively long time intervals can be exploited in a real-world application, namely the automatic identification of cover songs (i.e. different renditions or versions of the same musical piece). Importantly, this prediction strategy yields a parameter-free approach for cover song identification that is substantially faster, allows for reduced computational storage and still maintains highly competitive accuracies when compared to state-of-the-art systems.

Bubbles and capital flows

This paper presents a stylized model of international trade and asset price bubbles. Its central insight is that bubbles tend to appear and expand in countries where productivity is low relative to the rest of the world. These bubbles absorb local savings, eliminating inefficient investments and liberating resources that are in part used to invest in high productivity countries. Through this channel, bubbles act as a substitute for international capital flows, improving the international allocation of investment and reducing rate-of-return differentials across countries. This view of asset price bubbles could eventually provide a simple account of some real world phenomenae that have been difficult to model before, such as the recurrence and depth of financial crises or their puzzling tendency to propagate across countries.

Sistema d'adquisició de temperatures de 2 canals via R.F.

Poder mesurar i enregistrar diferents tipus de magnituds com pressió, força, temperatura etc. s’ha convertit en una necessitat per moltes aplicacions actuals. Aquestes magnituds poden tenir procedències molt diverses, tals com l’entorn, o poden ser generades per sistemes mecànics, elèctrics, etc. Per tal de poder adquirir aquestes magnituds, s’utilitzen els sistemes d’adquisició de dades. Aquests sistemes, prenen mostres analògiques del món real, i les transformen en dades digitals que poden ser manipulades per un sistema electrònic. Pràcticament qualsevol magnitud es pot mesurar utilitzant el sensor adient. Una magnitud molt utilitzada en sistemes d’adquisició de dades, és la temperatura. Els sistemes d’adquisició de temperatures estan molt generalitzats, i podem trobar-los com a sistemes, on l’objectiu és mostrar les dades adquirides, o podem trobar-los formant part de sistemes de control, aportant uns inputs necessaris per el seu correcte funcionament, garantir-ne l’estabilitat, seguretat etc. Aquest projecte, promogut per l’empresa Elausa, s’encarregarà d’adquirir, el senyal d’entrada de 2 Termoparells. Aquests mesuraran temperatures de circuits electrònics, que es trobaran dintre la càmera climàtica de Elausa, sotmesos a diferents condicions de temperatura, per tal de rebre l’homologació del circuit. El sistema haurà de poder mostrar les dades adquirides en temps real, i emmagatzemar-les en un PC que estarà ubicat en una oficina, situada a uns 30 m de distància de la sala on es farà el test. El sistema constarà d’un circuit electrònic que adquirirà, i condicionarà el senyal de sortida dels termoparells, per adaptar-lo a la tensió d’entrada d’un convertidor analògic digital, del microcontrolador integrat en aquesta placa. Seguidament aquesta informació, s’enviarà a través d’un mòdul transmissor de radiofreqüència, cap al PC on es visualitzaran les dades adquirides. Els objectius plantejats són els següents: - Dissenyar el circuit electrònic d’adquisició i condicionament del senyal. - Dissenyar, fabricar i muntar el circuit imprès de la placa d’adquisició. - Realitzar el programa de control del microcontrolador. - Realitzar el programa per presentar i desar les dades en un PC. - El sistema ha d’adquirir 2 temperatures, a través de Termoparells amb un rang d’entrada de -40ºC a +240ºC - S’ha de transmetre les dades via R.F. Els resultats del projecte han estat satisfactoris i s’han complert els objectius plantejats.

Reconstructing images from their most singular fractal manifold

Real-world images are complex objects, difficult to describe but at the same time possessing a high degree of redundancy. A very recent study [1] on the statistical properties of natural images reveals that natural images can be viewed through different partitions which are essentially fractal in nature. One particular fractal component, related to the most singular (sharpest) transitions in the image, seems to be highly informative about the whole scene. In this paper we will show how to decompose the image into their fractal components.We will see that the most singular component is related to (but not coincident with) the edges of the objects present in the scenes. We will propose a new, simple method to reconstruct the image with information contained in that most informative component.We will see that the quality of the reconstruction is strongly dependent on the capability to extract the relevant edges in the determination of the most singular set.We will discuss the results from the perspective of coding, proposing this method as a starting point for future developments.

To select or to weigh: a comparative study of linear combination schemes for superparent-one-dependence estimators

We conduct a large-scale comparative study on linearly combining superparent-one-dependence estimators (SPODEs), a popular family of seminaive Bayesian classifiers. Altogether, 16 model selection and weighing schemes, 58 benchmark data sets, and various statistical tests are employed. This paper's main contributions are threefold. First, it formally presents each scheme's definition, rationale, and time complexity and hence can serve as a comprehensive reference for researchers interested in ensemble learning. Second, it offers bias-variance analysis for each scheme's classification error performance. Third, it identifies effective schemes that meet various needs in practice. This leads to accurate and fast classification algorithms which have an immediate and significant impact on real-world applications. Another important feature of our study is using a variety of statistical tests to evaluate multiple learning methods across multiple data sets.

The EU-ADR Web Platform: delivering advanced pharmacovigilance tools

PURPOSE: Pharmacovigilance methods have advanced greatly during the last decades, making post-market drug assessment an essential drug evaluation component. These methods mainly rely on the use of spontaneous reporting systems and health information databases to collect expertise from huge amounts of real-world reports. The EU-ADR Web Platform was built to further facilitate accessing, monitoring and exploring these data, enabling an in-depth analysis of adverse drug reactions risks.METHODS: The EU-ADR Web Platform exploits the wealth of data collected within a large-scale European initiative, the EU-ADR project. Millions of electronic health records, provided by national health agencies, are mined for specific drug events, which are correlated with literature, protein and pathway data, resulting in a rich drug-event dataset. Next, advanced distributed computing methods are tailored to coordinate the execution of data-mining and statistical analysis tasks. This permits obtaining a ranked drug-event list, removing spurious entries and highlighting relationships with high risk potential.RESULTS: The EU-ADR Web Platform is an open workspace for the integrated analysis of pharmacovigilance datasets. Using this software, researchers can access a variety of tools provided by distinct partners in a single centralized environment. Besides performing standalone drug-event assessments, they can also control the pipeline for an improved batch analysis of custom datasets. Drug-event pairs can be substantiated and statistically analysed within the platform's innovative working environment.CONCLUSIONS: A pioneering workspace that helps in explaining the biological path of adverse drug reactions was developed within the EU-ADR project consortium. This tool, targeted at the pharmacovigilance community, is available online at https://bioinformatics.ua.pt/euadr/. Copyright © 2012 John Wiley & Sons, Ltd.

Market Index Biases and Minimum Risk Indices

Markets, in the real world, are not efficient zero-sum games where hypotheses of the CAPM are fulfilled. Then, it is easy to conclude the market portfolio is not located on Markowitz"s efficient frontier, and passive investments (and indexing) are not optimal but biased. In this paper, we define and analyze biases suffered by passive investors: the sample, construction, efficiency and active biases and tracking error are presented. We propose Minimum Risk Indices (MRI) as an alternative to deal with to market index biases, and to provide investors with portfolios closer to the efficient frontier, that is, more optimal investment possibilities. MRI (using a Parametric Value-at-Risk Minimization approach) are calculated for three stock markets achieving interesting results. Our indices are less risky and more profitable than current Market Indices in the Argentinean and Spanish markets, facing that way the Efficient Market Hypothesis. Two innovations must be outlined: an error dimension has been included in the backtesting and the Sharpe"s Ratio has been used to select the"best" MRI

Partial correlation : Network analysis

The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.