163 research outputs found

    Aplicando la metodología flipped-teaching en el Grado de Ingeniería Informática: una experiencia práctica

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    En el Grado de Ingeniería Informática de la Universitat Politècnica de València se llevó a cabo durante el curso 2014-15 una experiencia piloto de aplicación de la metodología Flipped-Teaching en todas las asigna-turas obligatorias de segundo curso del grado. La metodología Flipped-Teaching (o clase inversa) consiste en invertir el modelo tradicional de docencia, de modo que la lección magistral habitual de aula se sustituye por un conjunto de materiales en línea (vídeos, lecturas, etc.) que el alumno debe revisar previa a su asistencia a clase. Por su parte, las sesiones de aula se transforman en sesiones fundamental-mente prácticas, con actividades individuales o en grupo, pensadas principalmente para la resolución de ejercicios y problemas, la aclaración de dudas y la discusión sobre aspectos relevantes. En este trabajo se presenta la organización de la docencia, los métodos utilizados, así como la evaluación de la experiencia y los resultados obtenidos para una de las asignaturas del Grado de Ingeniería Informática en las que se aplicó esta metodología, en concreto "Concurrencia y Sistemas Distribuidos". La metodología Flipped-Teaching nos ha permitido aumentar la motivación y participación de los estudiantes así como mejorar su proceso de autoaprendizaje. La motivación de los alumnos ha sido enorme, reflejándose claramente tanto en su participación activa en la clase como por los buenos resultados de evaluación obtenidos

    Empowering users regarding the sensitivity of their data in social networks through nudge mechanisms

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    The use of online social networks (OSNs) is a continuous trade-off between relinquishing some privacy in exchange for getting some social benefits like maintaining (or creating new) relationships, getting support, influencing others’ opinions, etc. OSN users are faced with this decision each time they share information. The amount of information or its sensitivity is directly related to the amount of users’ loss of privacy. Currently, there are several approaches for assessing the sensitivity of the information based on the willingness of users to provide them, the monetary benefits derived from extracting knowledge of them, the amount of information they provide, etc. In this work, we focus on quantifying data sensitivity as the combination of all of the approaches and adapting them to the OSN domain. Furthermore, we propose a way of scoring publication sensitivity as the accumulative value of the sensitivity of the information types included in it. Finally, an experiment with 196 teenagers was carried out to assess the effectiveness of empowering users regarding the sensitivity of the publication. The results show a significant effect on users’ privacy behavior by the nudge message and the sensitivity included in it

    Using a Case-Based Reasoning Approach for Trading in Sports Betting Markets

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    The sports betting market has emerged as one of the most lucrative markets in recent years. Trading in sports betting markets entails predicting odd movements in order to bet on an outcome, whilst also betting on the opposite outcome, at different odds in order to make a profit, regardless of the final result. These markets are mainly composed by humans, which take decisions according to their past experience in these markets. However, human rational reasoning is limited when taking quick decisions, being influenced by emotional factors and offering limited calibration capabilities for estimating probabilities. In this paper, we show how artificial techniques could be applied to this field and demonstrate that they can outperform even the bevahior of high-experienced humans. To achieve this goal, we propose a case-based reasoning model for trading in sports betting markets, which is integrated in an agent to provide it with the capabilities to take trading decisions based on future odd predictions. In order to test the performance of the system, we compare trading decisions taken by the agent with trading decisions taken by human traders when they compete in real sports betting markets.This work has been partially supported by CONSOLIDER-INGENIO 2010 under grant CSD2007-00022, and project TIN2011-27652-C03-01. Juan M. Alberola has received a grant from Ministerio de Ciencia e Innovacion de Espana (AP2007-00289).Alberola Oltra, JM.; García Fornes, AM. (2013). Using a Case-Based Reasoning Approach for Trading in Sports Betting Markets. Applied Intelligence. 38(3):465-477. https://doi.org/10.1007/s10489-012-0381-9S465477383Aamodt A (1990) Knowledge-intensive case-based reasoning and sustained learning. In: Topics in case-based reasoning. Springer, Berlin, pp 274–288Aamodt A, Plaza E (1994) Case-based reasoning; foundational issues, methodological variations, and system approaches. AI Commun 7(1):39–59Ahn JJ, Byun HW, Oh KJ, Kim TY (2012) Bayesian forecaster using class-based optimization. Appl Intell 36(3):553–563Alberola JM, Garcia-Fornes A, Espinosa A (2010) Price prediction in sports betting markets. In: Proceedings of the 8th German conference on multiagent system technologies, pp 197–208Arias-Aranda D, Castro JL, Navarro M, Zurita JM (2009) A cbr system for knowing the relationship between flexibility and operations strategy. In: Proceedings of the 18th international symposium on foundations of intelligent systems, ISMIS’09, pp 463–472Ates C (2004) Prediction markets are only human: subadditivity in probability judgments. In: MSC in finance and international businessBerlemann M, Schmidt C (2001) Predictive accuracy of political stock markets—empirical evidence from a European perspective. Technical report 2001-57Betfair (2009) http://www.betfaircorporate.comChen Y, Goel S, Pennock D (2008) Pricing combinatorial markets for tournaments. In: STOC’08: proceedings of the 40th annual ACM symposium on theory of computing. ACM Press, New York, pp 305–314Debnath S, Pennock DM, Giles CL, Lawrence S (2003) Information incorporation in online in-game sports betting markets. In: Proceedings of the 4th ACM conference on electronic commerce, EC ’03. ACM Press, New York, pp 258–259. doi: 10.1145/779928.779987Fischoff B, Slovic P, Lichtenstein S (1977) Knowing with certainty: the appropriateness of extreme confidence. J Exp Psychol Human Percept Perform 3:552–564Forsythe R, Rietz T, Ross T (1999) Wishes, expectations and actions: a survey on price formation in election stock markets. J Econ Behav Organ 39(1):83–110Fortnow L, Kilian J, Pennock DM, Wellman MP (2005) Betting Boolean-style: a framework for trading in securities based on logical formulas. Decis Support Syst 39(1):87–104. doi: 10.1016/j.dss.2004.08.010Gayer G (2010) Perception of probabilities in situations of risk: a case based approach. Games Econ Behav 68(1):130–143Guo M, Pennock D (2009) Combinatorial prediction markets for event hierarchies. In: Proc of the 8th AAMAS’09. Int foundation for autonomous agents and multiagent systems, pp 201–208Huang W, Lai K, Nakamori Y, Wang S (2004) Forecasting foreign exchange rates with artificial neural networks: a review. Int J Inf Technol Decis Mak 3(1):145–165Hüllermeier E (2007) Case-based approximate reasoning. Theory and decision library, vol 44. Springer, BerlinKim K-J, Ahn H (2012) Simultaneous optimization of artificial neural networks for financial forecasting. Appl Intell 36(4):887–898LeBaron B (1998) Agent based computational finance: suggested readings and early research. J Econ Dyn ControlLiu Y, Yang C, Yang Y, Lin F, Du X, Ito T (2012) Case learning for cbr-based collision avoidance systems. Appl Intell 36(2):308–319Love BC (2008) Behavioural finance and sports betting markets. In: MSC in finance and international businessLuque C, Valls JM, Isasi P (2011) Time series prediction evolving Voronoi regions. Appl Intell 34(1):116–126Mantaras RLD, McSherry D, Bridge D, Leake D, Smyth B, Craw S, Faltings B, Maher M, Lou C, Forbus MCK, Keane M, Aamodt A, Watson I (2005) Retrieval, reuse, revision and retention in case-based reasoning. Knowl Eng Rev 20(3):215–240Moody J (1995) Economic forecasting: challenges and neural network solutions. In: Proceedings of the international symposium on artificial neural networksOntañón S, Plaza E (2009) Argumentation-based information exchange in prediction markets. Argument Multi-Agent Syst 5384:181–196Ontañón S, Plaza E (2011) An argumentation framework for learning, information exchange, and joint-deliberation in multi-agent systems. Multiagent Grid Syst 7:95–108Palmer R, Arthur W, Holland J, Lebaron B, Tayler P (1994) Artificial economic life: a simple model of a stock market. Physica D 75:264–274Pennock D, Debnath S, Glover E, Giles C (2002) Modelling information incorporation in markets, with application to detecting and explaining events. In: Proceedings of the 18th annual conference on uncertainty in artificial intelligence (UAI-02), San Francisco, CA. Morgan Kaufmann, San Mateo, pp 404–405Pennock DM, Lawrence S, Nielsen FÅ, Giles CL (2001) Extracting collective probabilistic forecasts from web games. In: Proceedings of the seventh ACM SIGKDD international conference on knowledge discovery and data mining, KDD ’01. ACM Press, New York, pp 174–183. doi: 10.1145/502512.502537Plott CR (2000) Markets as information gathering tools. South Econ J 67(1):2–15Qian B, Rasheed K (2007) Stock market prediction with multiple classifiers. 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    Assessing the Effectiveness of a Gamified Social Network for Applying Privacy Concepts: An Empirical Study with Teens

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    [EN] The concept of privacy in online social networks (OSNs) is a challenge, especially for teenagers. Previous works deal with teaching about privacy using educational online content, and media literacy. However, these tools do not necessarily promote less risky behaviors, and do not allow the assessment of users' behavior after the learning period. Moreover, few research studies about the effects of social gamification have been performed for this population segment (i.e., teenagers). To address this problem in this article, we propose the use of gamification in an OSN called Pesedia to facilitate the teaching/learning process, and assess its effectiveness in promoting suitable privacy behaviors. We tested our proposal comparing teenagers' performance in two editions of a course about social networks, and privacy (with, and without gamification) for one month. We measured the impact of gamification in the participants' behaviors toward privacy concepts as a consequence of the privacy teaching/learning process, and the participants' engagement in the educational process. The results show that there are significant differences in participants' behavior regarding privacy, and engagement in the gamified social network. Moreover, there is also a significant difference in participants' engagement for the gamified male participants. The gamified social network proposed in this article may be relevant, and useful for educators who wish to develop, and enhance teenagers' privacy skills, or for a broader base of aspects related to the development of digital competences, and technology in education.This work was supported in part by the Spanish Government Project TIN2017-89156-R, and in part by the FPI under Grant BFS-2015-074498. (Corresponding author: Elena Del Vol.)Alemany-Bordera, J.; Del Val, E.; García-Fornes, A. (2020). Assessing the Effectiveness of a Gamified Social Network for Applying Privacy Concepts: An Empirical Study with Teens. IEEE Transactions on Learning Technologies. 13(4):777-789. https://doi.org/10.1109/TLT.2020.3026584S77778913

    Multi-dimensional adaptation in MAS organizations

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    © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Organization adaptation requires determining the consequences of applying changes not only in terms of the benefits provided but also measuring the adaptation costs as well as the impact that these changes have on all of the components of the organization. In this paper, we provide an approach for adaptation in multiagent systems based on a multidimensional transition deliberation mechanism (MTDM). This approach considers transitions in multiple dimensions and is aimed at obtaining the adaptation with the highest potential for improvement in utility based on the costs of adaptation. The approach provides an accurate measurement of the impact of the adaptation since it determines the organization that is to be transitioned to as well as the changes required to carry out this transition. We show an example of adaptation in a service provider network environment in order to demonstrate that the measurement of the adaptation consequences taken by the MTDM improves the organization performance more than the other approaches.Manuscript received January 2, 2012; revised July 26, 2012; accepted August 7, 2012. Date of publication August 31, 2012; date of current version April 16, 2013. This work was supported in part by projects TIN2008-04446 and TIN2009-13839-C03-01. J. M. Alberola received a Grant from Ministerio de Ciencia e Innovacion de Espana (AP2007-00289). This paper was recommended by Associate Editor J. Huang.Alberola Oltra, JM.; Julian Inglada, VJ.; García-Fornes, A. (2013). Multi-dimensional adaptation in MAS organizations. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics. 43(2):622-633. https://doi.org/10.1109/TSMCB.2012.2213592S62263343

    Reaching unanimous agreements within agent-based negotiation teams with linear and monotonic utility functions

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    [EN] In this article, an agent-based negotiation model for negotiation teams that negotiate a deal with an opponent is presented. Agent-based negotiation teams are groups of agents that join together as a single negotiation party because they share an interest that is related to the negotiation process. The model relies on a trusted mediator that coordinates and helps team members in the decisions that they have to take during the negotiation process: which offer is sent to the opponent, and whether the offers received from the opponent are accepted. The main strength of the proposed negotiation model is the fact that it guarantees unanimity within team decisions since decisions report a utility to team members that is greater than or equal to their aspiration levels at each negotiation round. This work analyzes how unanimous decisions are taken within the team and the robustness of the model against different types of manipulations. An empirical evaluation is also performed to study the impact of the different parameters of the model.This work is supported by TIN2008-04446, PROMETEO/2008/051, TIN2009-13839-C03-01, CSD2007-00022 of the Spanish government, and FPU Grant AP2008-00600 awarded to Victor Sanchez-Anguix. This paper was recommended by Associate Editor X. Wang.Sanchez-Anguix, V.; Julian Inglada, VJ.; Botti, V.; García-Fornes, A. (2012). Reaching unanimous agreements within agent-based negotiation teams with linear and monotonic utility functions. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics. 42(3):778-792. https://doi.org/10.1109/TSMCB.2011.2177658S77879242

    Detection and nudge-intervention on sensitive information in social networks

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    [EN] Detecting sensitive information considering privacy is a relevant issue on Online Social Networks (OSNs). It is often difficult for users to manage the privacy associated with their posts on social networks taking into account all the possible consequences. The aim of this work is to provide information about the sensitivity of the content of a publication when a user is going to share it in OSN. For this purpose, we developed a privacy-assistant agent that detects sensitive information. Based on this information, the agent provides a message through a nudge mechanism warning about the possible risks of sharing the message. To avoid being annoying, the agent also considers the user's previous behaviour (e.g. if he previously ignored certain nudges) and adapts the messages it sends to give more relevance to those categories that are more important to the user from the point of view of the privacy risk. This agent was integrated into the social network Pesedia. We analysed the performance of different models to detect a set of sensitive categories (i.e. location, medical, drug/alcohol, emotion, personal attacks, stereotyping, family and association details, personal details and personally identifiable information) in a dataset of tweets in Spanish. The model that obtained the best results (i.e. F1 and accuracy) and that was finally integrated into the privacy-assistant agent was transformer-based.This work is supported by the Spanish Government project TIN2017-89156-R.Alemany, J.; Botti-Cebriá, V.; Del Val Noguera, E.; García-Fornes, A. (2022). Detection and nudge-intervention on sensitive information in social networks. Logic Journal of IGPL. 30(6):942-953. https://doi.org/10.1093/jigpal/jzac00494295330

    Distributed goal-oriented computing

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    For current computing frameworks, the ability to dynamically use the resources that are allocated in the network has become a key success factor. As long as the size of the network increases, it is more difficult to find how to solve the problems that the users are presenting. Users usually do know what they want to do, but they do not know how to do it. If the user knows its goals it could be easier to help him with a different approach. In this work we present a new computing paradigm based on goals. This paradigm is called Distributed goal-oriented computing paradigm. To implement this paradigm an execution framework for a goal-oriented operating system has been designed. In this paradigm users express their goals and the OS is in charge of helping the achievement of these goals by means of a service-oriented approach. © 2012 Elsevier Inc. All rights reserved.This work is supported by TIN2008-04446 and TIN2009-13839-C03-01 projects of the Spanish Government, PROMETEO/2008/051 project, FEDER funds and CONSOLIDER-INGENIO 2010 under grant CSD2007-00022.Palanca Cámara, J.; Navarro Llácer, M.; Julian Inglada, VJ.; García-Fornes, A. (2012). Distributed goal-oriented computing. Journal of Systems and Software. 85(7):1540-1557. https://doi.org/10.1016/j.jss.2012.01.045S1540155785

    VMFS: herramienta visual para la enseñanza del funcionamiento de un sistema de ficheros

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    Se ha desarrollado una herramienta que permite a los alumnos conocer de forma sencilla las distintas partes de que consta un sistema de ficheros en el sistema operativo MINIX. En concreto, mediante VMFS1 es posible estudiar cómo se gestiona en MINIX la asignación del espacio en disco a ficheros, así como las distintas estructuras de datos que se emplean en dicha gestión para implementar diferentes tipos de ficheros. Además, al tratarse de una intuitiva aplicación gráfica, resulta una herramienta muy adecuada para realizar prácticas en el marco de una asignatura orientada a la enseñanza de conceptos básicos y técnicas fundamentales de los sistemas operativos, cuyos alumnos normalmente carecen de grandes conocimientos de programación

    A Review on MAS-Based Sentiment and Stress Analysis User-Guiding and Risk-Prevention Systems in Social Network Analysis

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    [EN] In the current world we live immersed in online applications, being one of the most present of them Social Network Sites (SNSs), and different issues arise from this interaction. Therefore, there is a need for research that addresses the potential issues born from the increasing user interaction when navigating. For this reason, in this survey we explore works in the line of prevention of risks that can arise from social interaction in online environments, focusing on works using Multi-Agent System (MAS) technologies. For being able to assess what techniques are available for prevention, works in the detection of sentiment polarity and stress levels of users in SNSs will be reviewed. We review with special attention works using MAS technologies for user recommendation and guiding. Through the analysis of previous approaches on detection of the user state and risk prevention in SNSs we elaborate potential future lines of work that might lead to future applications where users can navigate and interact between each other in a more safe way.This work was funded by the project TIN2017-89156-R of the Spanish government.Aguado-Sarrió, G.; Julian Inglada, VJ.; García-Fornes, A.; Espinosa Minguet, AR. (2020). A Review on MAS-Based Sentiment and Stress Analysis User-Guiding and Risk-Prevention Systems in Social Network Analysis. Applied Sciences. 10(19):1-29. https://doi.org/10.3390/app10196746S1291019Vanderhoven, E., Schellens, T., Vanderlinde, R., & Valcke, M. (2015). Developing educational materials about risks on social network sites: a design based research approach. Educational Technology Research and Development, 64(3), 459-480. doi:10.1007/s11423-015-9415-4Teens and ICT: Risks and Opportunities. 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