EvoRecSys: Evolutionary framework for health and well-being recommender systems

Hugo Alcaraz-Herrera's PhD is supported by The Mexican Council of Science and Technology (Consejo Nacional de Ciencia y Tecnologia - CONACyT).In recent years, recommender systems have been employed in domains like ecommerce, tourism, and multimedia streaming, where personalising users’ experience based on their interactions is a fundamental aspect to consider. Recent recommender system developments have also focused on well-being, yet existing solutions have been entirely designed considering one single well-being aspect in isolation, such as a healthy diet or an active lifestyle. This research introduces EvoRecSys, a novel recommendation framework that proposes evolutionary algorithms as the main recommendation engine, thereby modelling the problem of generating personalised well-being recommendations as a multi-objective optimisation problem. EvoRecSys captures the interrelation between multiple aspects of well-being by constructing configurable recommendations in the form of bundled items with dynamic properties. The preferences and a predefined well-being goal by the user are jointly considered. By instantiating the framework into an implemented model, we illustrate the use of a genetic algorithm as the recommendation engine. Finally, this implementation has been deployed as a Web application in order to conduct a users’ study.Consejo Nacional de Ciencia y Tecnologia (CONACyT

Sistema multiagente para modelar procesos de consenso en toma de decisión en grupo a gran escala usando técnicas de soft computing

[ES]La presente Tesis se centra en el campo de los Procesos de Alcance de Consenso en Toma de Decisión en Grupo. En la literatura se han propuesto diversos modelos y enfoques para dar soporte a dichos procesos en problemas de toma de decisión en grupo reales, los cuales normalmente se han centrado en pequeños grupos de expertos. Sin embargo, dichos modelos presentan algunas dificultades:::;. y limitaciones para la gestión de grandes grupos. Dado que los problemas de toma de decisión en grupo a gran escala, en los que participa un elevado número de expertos, están cobrando una relevancia cada vez mayor en múltiples entornos tecnológicos, en esta investigación se propone un Sistema Multiagente basado en técnicas de soft computing, capaz de dar soporte en procesos de negociación semisupervisados, para alcanzar el consenso en problemas reales en los que participa un elevado número de expertos.[EN]This thesis focuses on the field of Consensus Reaching Processes within Group Decision Making. Several models and approaches have been proposed in the literature to support such processes in reallife group decision making problems, which have normally focused on small groups of experts. However, such models present some difficulties and limitations for the management of large groups. Due to the fact that large-scale group decision making problems, in which a large number of experts participate, are attaining an increasing relevance in multiple technological environments, this research proposes a multiagent system based on soft computing techniques, capable of giving support to semi-supervised negotiation processes in order to reach consensus in real-life problems in which a large number of experts take partoTesis Univ. Jaén. Departamento de Informática, leída el 25 de febrero de 201

A collaborative multiagent framework based on online risk-aware planning and decision-making

Planning is an essential process in teams of multiple agents pursuing a common goal. When the effects of actions undertaken by agents are uncertain, evaluating the potential risk of such actions alongside their utility might lead to more rational decisions upon planning. This challenge has been recently tackled for single agent settings, yet domains with multiple agents that present diverse viewpoints towards risk still necessitate compre- hensive decision making mechanisms that balance the utility and risk of actions. In this work, we propose a novel collaborative multi-agent planning framework that integrates (i) a team-level online planner under uncertainty that extends the classical UCT approximate algorithm, and (ii) a preference modelling and multi- criteria group decision making approach that allows agents to find accepted and rational solutions for planning problems, predicated on the attitude each agent adopts towards risk. When utilised in risk-pervaded scenarios, the proposed framework can reduce the cost of reaching the common goal sought and increase effectiveness, before making collective decisions by appropriately balancing risk and utility of actions

Sistema de Recomendación de Canciones OL-RadioUJA. Ampliación de Funcionalidades

La radio por Internet es un servicio con gran atractivo para los internautas en general, en cuyo ámbito destaca la reciente irrupción de radios personalizadas colaborativas, que ayudan al usuario a encontrar nueva música de su agrado, basándose en las preferencias de la música que ya ha escuchado el usuario. En 2009 fue presentada OL-RadioUJA, una radio personalizada sobre la que subyace un sistema de recomendación con filtrado colaborativo de canciones, las cuales se encuentran bajo algún tipo de licencia Creative Commons. La principal limitación de OL-RadioUJA es el reducido conjunto de canciones disponible, por lo que los usuarios, cansados de escuchar siempre las mismas canciones, dejaban de utilizar dicho servicio. En este artículo presentamos una nueva versión de OL-RadioUJA que contiene un nuevo módulo para incrementar la base de datos de canciones de la radio y así solventar la carencia del número de canciones. Para ello, dicho módulo permite que cualquier grupo musical pueda incorporar nuevas obras musicales (canciones) a OL-RadioUJA y gestionar el tipo licencia deseada para sus obras. Así, nuevas canciones son incorporadas a la radio colaborativa con la posibilidad de ser recomendadas a los usuarios. La inclusión de nuevas canciones origina el principal problema de los sistemas de recomendación con filtrado colaborativo: arranque frío o cold-start. En este artículo, presentaremos también una solución a dicho problema, la cual está basada en el género musical preferente de usuarios de OL-RadioUJA. Finalmente, nuevas funcionalidades relacionadas con las redes sociales que han sido incorporadas a la última versión de la radio serán presentadas

Consensus formation in opinion dynamics with online and offline interactions at complex networks

© 2018 World Scientific Publishing Company. Nowadays, with the development of information communication technology and Internet, more and more people receive information and exchange their opinions with others via online environments (e.g. Twitter, Facebook, Weibo, and WeChat). According to eMarketer Report [Worldwide Internet and Mobile Users: eMarketer's Updated Estimates and Forecast for 2015-2020 (eMarketer Report). Published October 11, 2016, https://www.emarketer.com/Report/Worldwide-Internet-Mobile-Users-eMarketers-Updated-Estimates-Forecast-20152020/2001897).], by the end of 2016, more than 3.2 billion individuals worldwide will use the Internet regularly, accounting for nearly 45% of the world population. By contrast, the other half of the global population still obtain information and regularly exchange their opinions in a more traditional way (e.g. face to face). Generally, the speed at which information spreads and opinions are exchanged and updated in an online environment is much faster than in an offline environment. This paper focuses on jointly investigating the challenge of consensus formation in opinion dynamics with online and offline interactions. Without loss of generality, we assume the speed at which information spreads and opinions are exchanged and updated in an online environment is T (T ) times as fast as in an offline environment. We demonstrate that the update speed ratio in mixed online and offline environments (i.e. T) strongly impacts the consensus formation at complex networks: a large update speed ratio of online and offline environments (i.e. T) makes it difficult for all agents to reach consensus in opinion dynamics. Furthermore, these effects are often further intensified as the number of online participating agents increases

Emergency and critical care professionals' opinion on escape room as a health sciences evaluation game: A cross-sectional descriptive study

New teaching and evaluation methods are growing in health sciences. The escape room is a game that is showing benefits for assessing knowledge and important competencies in healthcare professionals. The aim of this study is to analyse the opinion of emergency and critical care professionals on the use of escape rooms as an evaluation game.A quantitative, descriptive, cross-sectional study was conducted using an ad-hoc questionnaire with a Likert-type scale. The study included emergency and critical care professionals who participated in the escape room "The Frustrated Emergency and Critical Care Professional," that took place during an emergency and critical care national congress. Data collection was carried out in June 2019.The sample was composed of n = 50 emergency and critical care professionals, 52% of whom were physicians and 48% were nurses. Professionals believe that this is a good teaching game for evaluation and useful for strengthen knowledge (4.7 points), as well as to improve teamwork and the ability to work under pressure (4.9).The escape room is a useful evaluation game in the context of emergency and critical care units that also allows training the teamwork and working under pressure competencies.The authors want to thank SEMES for the opportunity of developing and executing the escape room during their congress

Invasive meningococcal disease: what we should know, before it comes back

Background: invasive meningococcal disease (IMD), sepsis and/or meningitis continues to be a public health problem, with mortality rates ranging from 5% to 16%. The aim of our study was to further knowledge about IMD with a large series of cases occurring over a long period of time, in a cohort with a high percentage of adult patients. Methods: observational cohort study of patients with IMD between 1977 hand 2013 at our hospital, comparing patients with only sepsis and those with meningitis and several degrees of sepsis. The impact of dexamethasone and prophylactic phenytoin was determined, and an analysis of cutaneous and neurological sequelae was performed. Results: a total of 527 episodes of IMD were recorded, comprising 57 cases of sepsis (11%) and 470 of meningitis with or without sepsis (89%). The number of episodes of IMD decreased from 352 of 527 (67%) in the first to 20 of 527 (4%) in the last quarter (P < .001). Thirty-three patients died (6%): 8 with sepsis (14%) and 25 with meningitis (5%) (P = .02). Cutaneous and neurological sequelae were present in 3% and 5% of survivors of sepsis and meningitis, respectively. The use of dexamethasone was safe and resulted in less arthritis, and patients given prophylactic phenytoin avoided seizures. Conclusions: the frequency of IMD has decreased sharply since 1977. Patients with sepsis only have the highest mortality and complication rates, dexamethasone use is safe and can prevent some arthritis episodes, and prophylactic phenytoin might be useful in a selected population. A rapid response and antibiotic therapy may help improve the prognosis