952 resultados para OpenFlow, SDN, Software-Defined Networking, Cloud
Resumo:
Référence bibliographique : Rol, 55042
Resumo:
Référence bibliographique : Rol, 55043
Resumo:
Este proyecto tiene como objetivo implementar un sistema libre bajo GNU/Linux para la recepción y evaluación de trabajos presentados a un congreso argentino sobre sistemas embebidos. Además, se piensa en un futuro en organizar un evento de software libre con revisión de pares, para lo cual sería coherente utilizar un sistema con licencia de software libre.
Resumo:
Desarrollo de software para el control de calidad y la generación automatizada de informes técnicos sobre ficheros de estado generados por AUV (vehículos autónomos submarinos).
Resumo:
L'objectiu principal de l'estudi és fer una avaluació d'una possible introducció a l'ERP d'un entorn complex de producció com pot ser el món de l'electrònica. Partirem de la hipòtesi que l'empresa vol substituir el software de gestió que fa servir actualment, i que ha estat desenvolupat internament, per plantejar la possibilitat d'introduir aquest entorn sota l'ERP actual o utilitzar un software de gestió de tercers.
Resumo:
Référence bibliographique : Rol, 55039
Resumo:
Référence bibliographique : Rol, 55038
Resumo:
Référence bibliographique : Rol, 55037
Resumo:
Référence bibliographique : Rol, 55036
Resumo:
Référence bibliographique : Rol, 55040
Resumo:
Este proyecto tiene como objetivo desarrollar las herramientas necesarias para poder crear un mapa conceptual de las aplicaciones de una organización, representar gráficamente este mapa y controlar el estado de cada aplicación. En concreto, se trata de desarrollar un formato XML que permita identificar y describir una aplicación, detallar con qué tecnología está desarrollada, qué componentes utiliza, especificar las interacciones o dependencias con otros sistemas, etc.
Resumo:
Quantitative or algorithmic trading is the automatization of investments decisions obeying a fixed or dynamic sets of rules to determine trading orders. It has increasingly made its way up to 70% of the trading volume of one of the biggest financial markets such as the New York Stock Exchange (NYSE). However, there is not a signi cant amount of academic literature devoted to it due to the private nature of investment banks and hedge funds. This projects aims to review the literature and discuss the models available in a subject that publications are scarce and infrequently. We review the basic and fundamental mathematical concepts needed for modeling financial markets such as: stochastic processes, stochastic integration and basic models for prices and spreads dynamics necessary for building quantitative strategies. We also contrast these models with real market data with minutely sampling frequency from the Dow Jones Industrial Average (DJIA). Quantitative strategies try to exploit two types of behavior: trend following or mean reversion. The former is grouped in the so-called technical models and the later in the so-called pairs trading. Technical models have been discarded by financial theoreticians but we show that they can be properly cast into a well defined scientific predictor if the signal generated by them pass the test of being a Markov time. That is, we can tell if the signal has occurred or not by examining the information up to the current time; or more technically, if the event is F_t-measurable. On the other hand the concept of pairs trading or market neutral strategy is fairly simple. However it can be cast in a variety of mathematical models ranging from a method based on a simple euclidean distance, in a co-integration framework or involving stochastic differential equations such as the well-known Ornstein-Uhlenbeck mean reversal ODE and its variations. A model for forecasting any economic or financial magnitude could be properly defined with scientific rigor but it could also lack of any economical value and be considered useless from a practical point of view. This is why this project could not be complete without a backtesting of the mentioned strategies. Conducting a useful and realistic backtesting is by no means a trivial exercise since the \laws" that govern financial markets are constantly evolving in time. This is the reason because we make emphasis in the calibration process of the strategies' parameters to adapt the given market conditions. We find out that the parameters from technical models are more volatile than their counterpart form market neutral strategies and calibration must be done in a high-frequency sampling manner to constantly track the currently market situation. As a whole, the goal of this project is to provide an overview of a quantitative approach to investment reviewing basic strategies and illustrating them by means of a back-testing with real financial market data. The sources of the data used in this project are Bloomberg for intraday time series and Yahoo! for daily prices. All numeric computations and graphics used and shown in this project were implemented in MATLAB^R scratch from scratch as a part of this thesis. No other mathematical or statistical software was used.
Resumo:
In this article we introduce JULIDE, a software toolkit developed to perform the 3D reconstruction, intensity normalization, volume standardization by 3D image registration and voxel-wise statistical analysis of autoradiographs of mouse brain sections. This software tool has been developed in the open-source ITK software framework and is freely available under a GPL license. The article presents the complete image processing chain from raw data acquisition to 3D statistical group analysis. Results of the group comparison in the context of a study on spatial learning are shown as an illustration of the data that can be obtained with this tool.
Resumo:
In the eighties, John Aitchison (1986) developed a new methodological approach for the statistical analysis of compositional data. This new methodology was implemented in Basic routines grouped under the name CODA and later NEWCODA inMatlab (Aitchison, 1997). After that, several other authors have published extensions to this methodology: Marín-Fernández and others (2000), Barceló-Vidal and others (2001), Pawlowsky-Glahn and Egozcue (2001, 2002) and Egozcue and others (2003). (...)
Resumo:
En aquest treball s’ha fet una avaluació comparativa dels resultats que es poden obtenir amb el software SpectraClassifier 1.0 (SC) desenvolupat al nostre grup de recerca, comparant‐lo amb l’SPSS, un programa estadístic informàtic estàndard, en un problema de classificació de tumors cerebrals humans amb dades d’espectroscopia de ressonància magnètica de protó (1H‐ERM). El interès d’aquesta avaluació comparativa radica en la documentació dels resultats obtinguts amb els dos sistemes quan en la correcció dels resultats obtinguts, així com ponderar la versatilitat i usabilitat dels dos paquets de software per a una aplicació concreta d’interès al treball del GABRMN. Per a aquest treball s’han utilitzat dades provinents de dos projecte europeus multicèntrics (INTERPRET i eTumour) en els quals vam participar. Les classes tumorals utilitzades (d’un total de 217 pacients) han sigut les majoritàries des del punt de vista epidemiològic: glioblastoma multiforme, metàstasi, astrocitomes de grau II, ligodendrogliomes de grau II, oligoastrocitomes de grau II i meningiomes de baix grau. Amb les dades d’aquests pacients s’han dissenyat classificadors basats en l’anàlisi discriminant lineal (LDA), s’han avaluat amb diferents mètodes matemàtics i s’han testat amb dades independents. Els resultats han estat satisfactoris, obtenint amb l’SC resultats més robusts amb dades independents respecte la classificació realitzada per l’SPSS.
