Open University of Madrid

Las Palmas de Gran Canaria, Spain

Open University of Madrid

Las Palmas de Gran Canaria, Spain
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Rodriguez D.,University of Alcalá | Sicilia M.A.,University of Alcalá | Sanchez-Alonso S.,University of Alcalá | Lezcano L.,University of Alcalá | And 2 more authors.
Interactive Learning Environments | Year: 2011

The online interaction of learners and tutors in activities with concrete objectives provides a valuable source of data that can be analyzed for different purposes. One of these purposes is the use of the information extracted from that interaction to aid tutors and learners in decision making about either the configuration of further learning activities or the filtering of learning resources. This article explores the use of an affiliation network model for such kind of purposes. Concretely, the use of techniques such as blockmodeling - a technique used to derive meaningful patterns of relationships in the network - and the analysis of m-slices - a technique helpful to study cohesion in relationships - are explored as tools to decide on the configuration of topics and/or learner groups. In particular, the results of the case study show that such techniques can be used to (i) filter participants for rearranging groups; (ii) rearrange topics of interest; and (iii) dynamically change the structure of a course. The techniques presented can be considered a case of collaborative filtering based on social network structure. © 2011 Taylor & Francis.


Gutierrez C.,Complutense University of Madrid | Garcia-Magarino I.,Open University of Madrid | Fuentes-Fernandez R.,Complutense University of Madrid
Engineering Applications of Artificial Intelligence | Year: 2011

Communication design is usually complex in Multi-Agent Systems (MAS) because of dynamic emergent behaviours. The lack of proper quantitative measures to assess alternative solutions and guide an iterative development makes this design even harder. The aim of this work is to efficiently find and describe communication patterns that should be avoided in these systems and identify the agents involved in these patterns. For this purpose, this research presents a suite of novel metrics and classification rules that, respectively, measure agents' communication and classify their results to describe patterns. This work also provides tools for automatically measuring the metrics and applying the classification rules. In order to evaluate this work, the results of applying these metrics and classification rules have been compared with the quality attribute of performance in several MAS. Performance is measured as the time between a user's request and the MAS response, and partially represents the factor of the quality of service. The experiments gather four agent-oriented communication designs that belong to two different domains: Crisis-management and Cinema ticket selling. The study reveals that the detected communication patterns are related with performance, and that the proposed metrics can arguably guide the design of communications improving the overall performance of systems. © 2010 Elsevier Ltd. All rights reserved.


Guillen-Gamez F.D.,Open University of Madrid | Garcia-Magarino I.,University of Zaragoza | Romero S.J.,Open University of Madrid
International Journal of Web-Based Learning and Teaching Technologies | Year: 2015

Currently, there is a demand within distance education of control mechanisms for verifying the identity of students when conducting activities within virtual classrooms. Biometric authentication is one of the tools to meet this demand and prevent fraud. In this line of research, the present work is aimed at analyzing the perceptions of a group of distance students on the impact on the teaching-learning process of a technology of biometric authentication called Smowl. To meet this objective the authors design a quasi-experimental study with two groups of 50 students, one using Smowl technology and the other not. The results show a comparison of the perceptions of both groups, finding that students who have used Smowl are more favorable towards the use of such tools, except in matters relating to the impact on academic performance and ethical aspects of its use, in which no significant differences were found. Copyright © 2015, IGI Global.


Guillen-Gamez F.D.,Open University of Madrid | Garcia-Magarino I.,University of Zaragoza
Journal of E-Learning and Knowledge Society | Year: 2015

Nowadays, one of the key challenges for distance education is to be able to verify the students’ identity in order to check if they are actually who they claim to be when they are doing their online tasks and to avoid identity thief. This can be achieved through facial authentication software. In e-learning, thanks to this technology there is a way to confirm that the students are not committing fraud in their studies and besides to improve this kind of education by equaling its validity and prestige to traditional face-to-face education. The goal of this research is to avoid fake users that perform educational tasks on behalf of others in the Learning Management Systems (LMSs), and more specifically to develop a new technique to design activities with glossaries that properly allow control of the student learning process through facial authentication software. The presented technique is composed of several steps that guide instructors in the elaboration of this kind of activities. This work has used Moodle platform for the experimentation, and analyzes the experience of 67 students with the activities designed with the presented technique. © 2015, Giunti. All rights reserved.


Ares J.,University of ruha | Lara J.A.,Open University of Madrid | Lizcano D.,Open University of Madrid | Suarez S.,University of ruha
Information Sciences | Year: 2016

Time series are sequences of data gathered over a period of time that emerge in different domains and whose analysis requires the application of specialized techniques, like, for example, data mining. Many existing time series data mining techniques, like the discrete Fourier transform (DFT), offer solutions for analysing whole time series. Often, however, it is more important to analyse certain regions of interest, known as events, rather than whole time series. Event identification is a highly complex task, as it is not always possible to determine with absolute certainty whether or not a segment of a time series is an event. In such cases, the best practice is to establish the certainty of this segment being a time series event, thus outputting a fuzzy set of events. In this paper we propose a framework that is capable of identifying events and establishing the degree of certainty that a domain expert would assign to the identified events based on a previous training process assisted by a panel of experts. Having identified the events, the proposed framework can be used to classify time series. This is done by means of a process that combines time series comparison and time series reference model generation by analysing the events contained in the respective time series and the certainties of the identified events. The proposed framework is an evolution of an earlier framework that we developed which did not apply soft computing techniques to identify and manage the time series events. We have used our framework to classify times series generated in the electroencephalography (EEG) area. EEG is a neurological exploration used to diagnose nervous system disorders. The performance of the framework was evaluated in terms of classification accuracy. The results confirmed that, thanks to the use of soft computing techniques, the new framework substantially improves the time series classification results of its predecessor. © 2015 Elsevier Inc All rights reserved.


Pascual R.D.M.,Rey Juan Carlos University | Casado E.M.,Open University of Madrid
AIP Conference Proceedings | Year: 2014

Despite its lack of definition, in a general sense, knowledge management (KM) is consubstantial to contemporary innovation-driven social systems (IDSSs), allowing individuals, organizations, and entire societies, to cope with their intrinsic technical uncertainties more effectively. Before the advent of IDSSs, most of the results of KM were considered naturally inappropriable as well as fractions of the public domain. In such context, patents litigation was almost anecdotic. This paper summarizes various social scientific and humanistic approaches that nourish the emergence of a new KM model in which innovation will be anchored in the claim for universality. Patentability of ICT and services is also considered on the realm of a commons-based KM. © 2014 AIP Publishing LLC.


Lizcano D.,Open University of Madrid | Alonso F.,Technical University of Madrid | Soriano J.,Technical University of Madrid | Lopez G.,Technical University of Madrid
Journal of Systems and Software | Year: 2014

Enabling real end-user development is the next logical stage in the evolution of Internet-wide service-based applications. Successful composite applications rely on heavyweight service orchestration technologies that raise the bar far above end-user skills. This weakness can be attributed to the fact that the composition model does not satisfy end-user needs rather than to the actual infrastructure technologies. In our opinion, the best way to overcome this weakness is to offer end-to-end composition from the user interface to service invocation, plus an understandable abstraction of building blocks and a visual composition technique empowering end users to develop their own applications. In this paper, we present a visual framework for end users, called FAST, which fulfils this objective. FAST implements a novel composition model designed to empower non-programmer end users to create and share their own self-service composite applications in a fully visual fashion. We projected the development environment implementing this model as part of the European FP7 FAST Project, which was used to validate the rationale behind our approach. © 2014 Elsevier Inc.


Lizcano D.,Open University of Madrid | Alonso F.,Technical University of Madrid | Soriano J.,Technical University of Madrid | Lopez G.,Technical University of Madrid
Information and Software Technology | Year: 2015

Context: This paper addresses one of the major end-user development (EUD) challenges, namely, how to pack today's EUD support tools with composable elements. This would give end users better access to more components which they can use to build a solution tailored to their own needs. The success of later end-user software engineering (EUSE) activities largely depends on how many components each tool has and how adaptable components are to multiple problem domains. Objective: A system for automatically adapting heterogeneous components to a common development environment would offer a sizeable saving of time and resources within the EUD support tool construction process. This paper presents an automated adaptation system for transforming EUD components to a standard format. Method: This system is based on the use of description logic. Based on a generic UML2 data model, this description logic is able to check whether an end-user component can be transformed to this modelling language through subsumption or as an instance of the UML2 model. Besides it automatically finds a consistent, non-ambiguous and finite set of XSLT mappings to automatically prepare data in order to leverage the component as part of a tool that conforms to the target UML2 component model. Results: The proposed system has been successfully applied to components from four prominent EUD tools. These components were automatically converted to a standard format. In order to validate the proposed system, rich internet applications (RIA) used as an operational support system for operators at a large services company were developed using automatically adapted standard format components. These RIAs would be impossible to develop using each EUD tool separately. Conclusion: The positive results of applying our system for automatically adapting components from current tool catalogues are indicative of the system's effectiveness. Use of this system could foster the growth of web EUD component catalogues, leveraging a vast ecosystem of user-centred SaaS to further current EUSE trends. © 2014 Elsevier B.V. All rights reserved.


Vavassori S.,Technical University of Madrid | Soriano J.,Technical University of Madrid | Lizcano D.,Open University of Madrid | Jimenez M.,Technical University of Madrid
Sensors (Switzerland) | Year: 2013

Although context could be exploited to improve performance, elasticity and adaptation in most distributed systems that adopt the publish/subscribe (P/S) communication model, only a few researchers have focused on the area of context-aware matching in P/S systems and have explored its implications in domains with highly dynamic context like wireless sensor networks (WSNs) and IoT-enabled applications. Most adopted P/S models are context agnostic or do not differentiate context from the other application data. In this article, we present a novel context-aware P/S model. SilboPS manages context explicitly, focusing on the minimization of network overhead in domains with recurrent context changes related, for example, to mobile ad hoc networks (MANETs). Our approach represents a solution that helps to efficiently share and use sensor data coming from ubiquitous WSNs across a plethora of applications intent on using these data to build context awareness. Specifically, we empirically demonstrate that decoupling a subscription from the changing context in which it is produced and leveraging contextual scoping in the filtering process notably reduces (un)subscription cost per node, while improving the global performance/throughput of the network of brokers without altering the cost of SIENA-like topology changes. © 2013 by the authors; licensee MDPI, Basel, Switzerland.


Burgos M.C.,Open University of Madrid | Campanario M.L.,Open University of Madrid | Lara J.A.,Open University of Madrid | Lizcano D.,Open University of Madrid
Lecture Notes in Engineering and Computer Science | Year: 2015

The filmmaking is one of the most important branches of the entertainment industry primarily because of the huge revenues that it generates. The producer plays an essential role in filmmaking, as they provide the funding required to turn out quality blockbusters for cinemagoers. Film production is a risky business, as illustrated by the examples of films that fail to cover costs every year. In this respect, tools capable of predicting movie profitability are of potential use to producers as a decision-making tool for deciding whether or not to produce a movie project. In this paper we report a study using historical data on over 100 films produced in the United States (including their genre, opening month, duration, budget, etc.). Decision trees were extracted from these data in order to forecast whether or not a film will be profitable even before it is produced. Decision trees are models commonly used in the field of artificial intelligence as decision support tools. The results show that the resulting model forecasts whether or not a movie will be profitable with an accuracy of over 70%, and this model can be used as a decision support tool for film producers. The proposed approach is not designed to be used as a standalone tool; it should rather round out other forecasting methods, including producers' foresight and judgement. The approach presented here could be equally applicable to other branches of the entertainment business, such as the music or video game industries.

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