Search

Due to the large, heterogeneous audience of Web applications, and its rapidly changing expectations, holistic requirement analysis approaches are crucial to ensure the success of Web engineering projects. To increase the quality of resulting Web applications, non-functional requirements (NFRs) must be considered. Satisfying them is a non-trivial task that depends on making decisions about which functional requirements (FRs) to implement, and how to prioritize the NFRs. A satisfactory solution is a trade-off, where competing NFRs must be balanced. In this paper, we outline how the Pareto efficiency can complement a goal-oriented requirement analysis modelling to evaluate and select optimal configurations of requirements for a Web application, while NFRs are balanced and maximized according to a priority list. We hereby focus on an empirical evaluation to verify whether our Pareto method improves the accuracy of design decisions during the requirements analysis phase, and/or if it reduces the time needed by designers. Este trabajo ha sido parcialmente financiado por los siguientes proyectos: Open.Mind (GV/2014/098) de la Generalitat Valenciana; PROFAPI2012/002 y PROFAPI2013/002 de la Universidad Autónoma de Sinaloa, México y MANTRA (GRE09-17) de la Universidad de Alicante.

This paper deals with the application and optimization of active loops to mitigate the magnetic field generated by medium voltage/low voltage (MV/LV) substations. In particular, two active loops configurations are analyzed in several regions located around and above a particular MV/LV substation. An optimization process, based on a genetic algorithm, is applied in order to reduce the average magnetic field inside each region to the minimum, obtaining the optimum geometry of the loops and the currents to be injected. The performance of the proposed active loops is compared, highlighting their main advantages and disadvantages regarding its application to MV/LV substations

In this paper, we present a study about Si and GaAs space solar cells by means of numerical simulations. We have investigated the variations of the short-circuit current, open circuit voltage and maximum power point, before and after the devices were irradiated with 10 MeV protons and fluences between 109 and 1013 p+ /cm2. The simulation results allow to obtain the optimum solar cell with specific requirements for space applications. Fil: Cappelletti, Marcelo Ángel. Universidad Nacional de La Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Casas, Guillermo. Universidad Nacional de La Plata; Argentina. Universidad Nacional de Quilmes; Argentina Fil: Cedola, Ariel Pablo. Universidad Nacional de La Plata; Argentina Fil: Peltzer y Blanca, Eitel Leopoldo. Universidad Nacional de La Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

Internet Traffic Classification aims at the identification of the Internet application that generates a given sequence of packets. Shallow Packet Inspection (SPI) is a new family of classification techniques that only use information available in the external header of packets and the statistical characterization of the traffic process. Therefore, these techniques are applicable even to encrypted or obfuscated traffic. The packet arrival process is a particularly interesting features for traffic classification, as it is difficult to significantly modify it. This paper proposes a classification technique based on a classification feature called Index of Variability, which evaluates the traffic source burstiness over various time scales in order to discriminate among different classes of Internet applications. Experimental results show that this classification method operates effectively both on synthetic and real traffic traces. Synthetic traffic traces make it possible to estimate the classification error rate achieved by the classification algorithm. The usage of real traces allows us to compare the performance of the method to the performance obtained with Deep Packet Inspection (DPI) techniques, showing that SPI and DPI yields similar results.

Data warehouses integrate several operational sources to provide a multidimensional analysis of data, thus improving the decision making process. Therefore, an in-depth analysis of these data sources is crucial for data warehouse development. Traditionally, this analysis has been based on a set of informal guidelines or heuristics to support the manually discovery of multidimensional elements on a well-known documentation. Therefore, this task may become highly tedious and prone to fail. In this paper, MDA (Model Driven Architecture) is used to design a reverse engineering process in which the following tasks are performed (i) obtain a logical representation of data sources (ii) mark this logical representation with multidimensional concepts, and (iii) derive a conceptual multidimensional model from the marked model. Este trabajo ha sido financiado por los proyectos METASIGN (TIN2004-00779) del Ministerio de Educación y Ciencia y DADS(PBC-05-012-2) de la Consejería de Educación y Ciencia de Castilla-La Mancha. J.-N. Mazón dispone de una beca FPU (AP2005-1360) del Ministerio de Educación y Ciencia.