Un model d'implantació d'un sistema de gestió de la documentació administrativa: el projecte DursiGED

[cat] Aquest article descriu el procés d'implantació d'un sistema de gestió de la documentació administrativa al Departament d'Universitats, Recerca i Societat de la Informació de la Generalitat de Catalunya (actualment Departament d'Innovació, Universitats i Empresa). El projecte, anomenat DursiGED, ha inclòs l'anàlisi, el desenvolupament i la implantació dels productes i serveis necessaris per gestionar la documentació electrònica i en suport paper de manera normalitzada i d'acord amb uns paràmetres de qualitat. L'article inclou la descripció de la planificació del projecte, el procés d'implantació i seguiment, i els productes i serveis que n'han resultat.

Preface: Extreme events induced by weather and climate change: evaluation, forecasting and proactive planning

This special issue of Natural Hazards and Earth System Sciences (NHESS) contains eight papers presented as oral or poster contributions in the Natural Hazards NH-1.2 session on"Extreme events induced by weather and climate change: evaluation, forecasting and proactive planning", held at the European Geosciences Union (EGU) General Assembly in Vienna, Austria, on 13-18 April 2008. The aim of the session was to provide an international forum for presenting new results and for discussing innovative ideas and concepts on extreme hydro-meteorological events, including: (i) the assessment of the risk posed by the extreme events, (ii) the expected changes in the frequency and intensity of the events driven by a changing climate and by multiple human- induced causes, (iii) new modelling approaches and original forecasting methods to predict extreme events and their consequences, and (iv) strategies for hazard mitigation and risk reduction, and for a improved adaptation to extreme hydro-meteorological events ...

Design and evaluation of learning algorithms for dynamic resource management in virtual networks

Network virtualisation is considerably gaining attentionas a solution to ossification of the Internet. However, thesuccess of network virtualisation will depend in part on how efficientlythe virtual networks utilise substrate network resources.In this paper, we propose a machine learning-based approachto virtual network resource management. We propose to modelthe substrate network as a decentralised system and introducea learning algorithm in each substrate node and substrate link,providing self-organization capabilities. We propose a multiagentlearning algorithm that carries out the substrate network resourcemanagement in a coordinated and decentralised way. The taskof these agents is to use evaluative feedback to learn an optimalpolicy so as to dynamically allocate network resources to virtualnodes and links. The agents ensure that while the virtual networkshave the resources they need at any given time, only the requiredresources are reserved for this purpose. Simulations show thatour dynamic approach significantly improves the virtual networkacceptance ratio and the maximum number of accepted virtualnetwork requests at any time while ensuring that virtual networkquality of service requirements such as packet drop rate andvirtual link delay are not affected.