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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.

Assistance to people during rehabilitation has to be adapted to their needs. Too little help can lead to frustration and stress in the user; an excess of help may lead to low participation and loss of residual skills. Robotic rollators may adapt assistance. The main challenge to cope with this issue is to estimate how much help is needed on the fly, because it depends not only on the person condition, but also on the specific situation that they are negotiating. Clinical scales provide a global condition based estimation, but no local estimator based on punctual needs. Condition also changes in time, so clinical scales need to be recalculated again and again. In this paper we propose a novel approach to estimate users’ condition in a continuous way via a robotic rollator. Our work focuses on predicting the value of the well known Tinetti Mobility test from spatiotemporal gait parameters obtained from our platform while users walk. This prediction provides continuous insight on the condition of the user and could be used to modify the amount of help provided. The proposed method has been validated with 19 volunteers at a local hospital that use a rollator for rehabilitation. All volunteers presented some physical or mental disabilities. Our results sucessfully show a high correlation of spatiotemporal gait parameters with Tinetti Mobility test gait (R2 = 0.7) and Tinetti Mobility test balance (R2 = 0.6). Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.

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.

6 págs, 1 fig.-- Publicado en la Sección: "Artículos seleccionados de IEEE ICALT" (ICALT'2008 - Eighth IEEE International Conference on Advanced Learning Technologies, Santander, Cantabria, Spain, Jul 1-5, 2008). Previamente publicado como ponencia (en inglés) en: Proceedings ICALT'08 - Eighth IEEE International Conference on Advanced Learning Technologies, 2008, p. 278-282, http://e-archivo.uc3m.es/handle/10016/8964 Collaborative learning models are widely used in educational institutions. These models require a high interaction level among students and are mainly oriented towards in-class scenarios. But when collaborative models are deployed in a distant scenario, user expressiveness is significantly reduced thus creating a gap that hinders the effectiveness of this collaboration. A computer-supported model provides a set of tools to compensate for the distant scenario and reduce this gap. This paper presents the issues and solutions derived from the design and deployment of a complex collaborative model in a distant scenario. The course structure was captured using the Learning Design specification, and an architecture based on Virtual Network Computing was used to provide the required collaborative tools. The course was included as part of a regular undergraduate program in three higher educational institutions. Trabajo parcialmente financiado por el Programa Nacional de Tecnologías de la Información y de las Comunicaciones, Proyectos MOSAIC (TSI2005-08225-C07-02/04) y LEARN3 (TIN2008-05163/TSI). Publicado

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.

Postprint This paper describes an object-oriented approach for handling complex industrial automation systems. The proposed approach relies on relationships between modeling perspectives and integrates different models of existing object-oriented methodologies. It therefore supports the multi-disciplinary character of industrial automation projects. A framework based on the concept of viewpoints is also presented.