Personalised e-learning, semantic web and learning ontologies

Kurzel(2004) points out that researchers in e-learning and educational technologists, in a quest to provide improved Learning Environments (LE) for students are focusing on personalising the experience through a Learning Management System (LMS) that attempts to tailor the LE to the individual (see amongst others Eklund & Brusilovsky, 1998; Kurzel, Slay, & Hagenus, 2003; Martinez,2000; Sampson, Karagiannidis, & Kinshuk, 2002; Voigt & Swatman; 2003). According to Kurzel (2004) this tailoring can have an impact on content and how it’s accessed; the media forms used; method of instruction employed and the learning styles supported. This project is aiming to move personalisation forward to the next generation, by tackling the issue of Personalised e-Learning platforms as pre-requisites for building and generating individualised learning solutions. The proposed development is to create an e-learning platform with personalisation built-in. This personalisation is proposed to be set from different levels of within the system starting from being guided by the information that the user inputs into the system down to the lower level of being set using information inferred by the system’s processing engine. This paper will discuss some of our early work and ideas.

Social networks and cooperative learning in a MOOC

MOOCs are changing the educational landscape and gaining a lot of attention in scientific literature. However, the pedagogical design of these proposals has been called into question. It is precisely MOOCs’ social aspect, i.e. the interaction between course participants and the support for learning processes that has become one of the main topics of interest. This article presents the results of a research project carried out at the University of the Basque Country, which focused in cooperative learning and the intensive use of social networks in a MOOC. Significant data was compiled through Likert-type surveys, revealing that the use of both external and internal social networks in a massive open online course is a factor that is evaluated positively by students. We argue that the use of social networks as a learning strategy in a MOOC has an influence on academic performance and on the students' success rate. Furthermore, the participants’ age also has a bearing on the social networks they use, and we have found that the younger members tend to work with external networks such as Twitter or personal blogs, whereas the older students are more inclined to use forums from the Chamilo or Ning platforms.

Learning Bayesian Networks with Bounded Tree-Width via Guided Search

Bounding the tree-width of a Bayesian network can reduce the chance of overfitting, and allows exact inference to be performed efficiently. Several existing algorithms tackle the problem of learning bounded tree-width Bayesian networks by learning from k-trees as super-structures, but they do not scale to large domains and/or large tree-width. We propose a guided search algorithm to find k-trees with maximum Informative scores, which is a measure of quality for the k-tree in yielding good Bayesian networks. The algorithm achieves close to optimal performance compared to exact solutions in small domains, and can discover better networks than existing approximate methods can in large domains. It also provides an optimal elimination order of variables that guarantees small complexity for later runs of exact inference. Comparisons with well-known approaches in terms of learning and inference accuracy illustrate its capabilities.

Privacidad e intimidad en las interacciones virtuales

El presente trabajo es una revisión de la literatura de investigación en Ciberpsicología centrada en las categorías de privacidad, intimidad, identidad y vulnerabilidad, y en la forma como estas se desarrollan en las redes sociales virtuales. Los principales hallazgos indicaron que son los jóvenes quienes dedican gran parte de su tiempo a interactuar en dichas redes, y a su vez, dado el manejo que les dan, tienen mayor exposición ante los posibles riesgos de estas, como el matoneo, las conductas auto lesivas, la explotación sexual y los trastornos de la alimentación. Se describen estos riesgos y se proponen posibles soluciones.

Incidencia y factores asociados a infecciones bacterianas en el primer mes postrasplante hepático en la Fundación Cardioinfantil

Introducción: El trasplante hepático ortotópico es la colocación de un nuevo hígado en la misma ubicación del explantado. El objetivo es prolongar la duración y la calidad de vida en pacientes con enfermedades hepáticas terminales. Sin embargo, las infecciones bacterianas son una complicación en los pacientes receptores del trasplante, comprometiendo el éxito del procedimiento. El objetivo fue determinar los factores asociados a infecciones bacterianas en el primer mes tras realizada la intervención y describir las características demográficas de esa población. De 332 trasplantes realizados, que 262 cumplieron criterios para el análisis. Métodos: Se realizó un estudio observacional analítico de casos y controles anidado en una cohorte, en mayores de 18 años, receptores de trasplante hepático primario, de la FCI-IC de 2005 a 2014; excluyendo trasplante combinado hígado riñón, retrasplantes o fallecidos por causa diferente a la infecciosa durante el primer mes. Resultados: Se encontró que la ventilación mecánica por más de 1 día, el catéter venoso central mayor de 3 días son los principales factores de riesgo para infecciones bacterianas. La albúmina mayor de 2,6gr/dl se asoció a menor infección. Los agentes etiológicos predominantes fueron gérmenes gram negativos como E. coli, K. pneumonia y E. cloacae. Mientras que bacteremia, infección urinaria y peritonitis fueron las infecciones más frecuentes. La incidencia de infección bacteriana en esta población fue 24%. Discusión: Se recomienda por tanto extubación antes de 24 horas, uso de catéter central menor de 3 días y limitar el uso del catéter vesical.

Oro para Colombia

Las mujeres han debido atravesar un largo camino partiendo de la discriminación hasta empezar un proceso de equidad en la sociedad y en el deporte, de esta manera llegar a ser parte de un evento como los Juegos Olímpicos. Esta tesis toma el caso de tres atletas colombianas y describe su proceso de formación para lograr dos medallas de oro para el país.

ECG arrhythmia classification based on optimum-path forest

An important tool for the heart disease diagnosis is the analysis of electrocardiogram (ECG) signals, since the non-invasive nature and simplicity of the ECG exam. According to the application, ECG data analysis consists of steps such as preprocessing, segmentation, feature extraction and classification aiming to detect cardiac arrhythmias (i.e.; cardiac rhythm abnormalities). Aiming to made a fast and accurate cardiac arrhythmia signal classification process, we apply and analyze a recent and robust supervised graph-based pattern recognition technique, the optimum-path forest (OPF) classifier. To the best of our knowledge, it is the first time that OPF classifier is used to the ECG heartbeat signal classification task. We then compare the performance (in terms of training and testing time, accuracy, specificity, and sensitivity) of the OPF classifier to the ones of other three well-known expert system classifiers, i.e.; support vector machine (SVM), Bayesian and multilayer artificial neural network (MLP), using features extracted from six main approaches considered in literature for ECG arrhythmia analysis. In our experiments, we use the MIT-BIH Arrhythmia Database and the evaluation protocol recommended by The Association for the Advancement of Medical Instrumentation. A discussion on the obtained results shows that OPF classifier presents a robust performance, i.e.; there is no need for parameter setup, as well as a high accuracy at an extremely low computational cost. Moreover, in average, the OPF classifier yielded greater performance than the MLP and SVM classifiers in terms of classification time and accuracy, and to produce quite similar performance to the Bayesian classifier, showing to be a promising technique for ECG signal analysis. © 2012 Elsevier Ltd. All rights reserved.

El carácter estructural de los programas del desarrollo urbano: una introducción a la naturaleza social de la estructura urbana y a los efectos espaciales urbanos del patrón de desarrollo

Ponencia presentada a la Reunión Continental sobre la Ciencia y el Hombre organizada por la American Society for the Advancement of Sciences y el CONACYT de México, en la ciudad de México del 24 de junio al 4 de julio de 1973