Text2Emotion: un gestor d'experiències SOA : extracció d'emocions per al suport a la gestió de relació amb clients

Customer Experience Management (CEM) se ha convertido en un factor clave para el éxito de las empresas. CEM gestiona todas las experiencias que un cliente tiene con un proveedor de servicios o productos. Es muy importante saber como se siente un cliente en cada contacto y entonces poder sugerir automáticamente la próxima tarea a realizar, simplificando tareas realizadas por personas. En este proyecto se desarrolla una solución para evaluar experiencias. Primero se crean servicios web que clasifican experiencias en estados emocionales dependiendo del nivel de satisfacción, interés, … Esto es realizado a través de minería de textos. Se procesa y clasifica información no estructurada (documentos de texto) que representan o describen las experiencias. Se utilizan métodos de aprendizaje supervisado. Esta parte es desarrollada con una arquitectura orientada a servicios (SOA) para asegurar el uso de estándares y que los servicios sean accesibles por cualquier aplicación. Estos servicios son desplegados en un servidor de aplicaciones. En la segunda parte se desarrolla dos aplicaciones basadas en casos reales. En esta fase Cloud computing es clave. Se utiliza una plataforma de desarrollo en línea para crear toda la aplicación incluyendo tablas, objetos, lógica de negocio e interfaces de usuario. Finalmente los servicios de clasificación son integrados a la plataforma asegurando que las experiencias son evaluadas y que las tareas de seguimiento son automáticamente creadas.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Mòdul per a Moodle que possibilita la utilització de mapes conceptuals als creadors de cursos.

Actualment, i amb la ràpida expansió en el món educatiu de les plataformes d'aprenentatge virtual, s'experimenta una demanda de funcionalitats que puguen ser usades des d'aquestes plataformes i que donen resposta als reptes educatius dins d'aquest nou paradigma d'aprenentatge.En aquest treball s'ha fet una tasca d'integració d'eines que possibiliten la creació, modificació, visualització i magatzematge de mapes conceptuals dins d'una plataforma d'aprenentatge molt usada actualment, tant en ensenyament secundari com universitari. La plataforma moodle.L'eina per construir mapes conceptuals triada ha segut l'anomenada VUE, desenvolupada en la universitat de Tufts.Ambdues eines moodle i VUE s'han desenvolupat amb codi obert i baix llicències de programari lliure, així es poden tindre tots els avantatges que aquestes llicències proporcionen.El resultat és una integració que possibilita la utilització de mapes conceptuals dins de la plataforma moodle.

Desenvolupament d'un gestor de trobades, reunions i convocatòries usant la plataforma WAC

Anàlisi, disseny, implementació i documentació d'una aplicació per a dispositius mòbils utilitzant la plataforma WAC.

Treball Final de Carrera .NET : plataforma per a la gestió d'un servei de lloguer de vehicles

Plataforma per a la gestió d'un servei de lloguer de vehicles desenvolupat en tecnologia .Net de Microsoft.Consta d'una plana web enfocada als clients, una aplicació d'administració i d'una aplicació mòbil per a la gestió per part del personal de taller.

Creació d'una plataforma LAMP mitjançant Puppet

Implementació del sistema de gestió de configuracions Puppet per configurar desde zero una plataforma LAMP.

Plataforma informática integral basada en tecnología GNU/Linux para negocio online de repostería casera

Plataforma informática integral para negocio online de repostería casera basada en tecnología Linux (opensource).

Estudi i desenvolupament d'un sistema automatitzat d'elaboració d'exercicis estadístics per a la plataforma Moodle

El projecte es basa en desenvolupar una solució per a la integració dins de la plataforma Moodle, d'un formulari que permeti sol·licitar, als usuaris registrats, exercicis dels indicadors estadístics més comuns, i escollir-ne el nivell de dificultat. La creació dels exercicis i la solució dels mateixos, es durà a terme en el moment de la seva sol·licitud, a través d'un procediment automatitzat que generarà dades aleatòries dins d'un rang determinat. El procediment automatitzat es realitzarà mitjançant la funció "Sweave" del programari estadístic R. Aquesta funció integra en un únic document els continguts de text del programari LaTeX amb els continguts estadístics provinents de R.

Adult Learning Services

Evidence Review 4 - Adult learning services Briefing 4 - Adult learning services This pair of documents, commissioned by Public Health England, and written by the UCL Institute of Health Equity, address the role of participation in learning as an adult in improving health. There is evidence that involvement in adult learning has both direct and indirect links with health, for example because it increases employability. There is some evidence that those who are lower down the social gradient benefit most, in health terms, from adult learning. However, there is a gradient both in participation in adult learning and skill level, whereby the more someone would benefit from adult learning, the less likely they are to participate, and the lower their literacy and numeracy skills are likely to be. This is due to a range of barriers, including prohibitively high costs, lack of personal confidence, or lack of availability and access. These papers also show that there are a number of actions local authorities can take to increase access to adult learning, improve quality of provision and increase the extent to which it is delivered and targeted proportionate to need. The full evidence review and a shorter summary briefing are available to download above. This document is part of a series. An overview document which provides an introduction to this and other documents in the series, and links to the other topic areas, is available on the ‘Local Action on health inequalities’ project page. A video of Michael Marmot introducing the work is also available on our videos page.

Substance use behaviours of young people with a moderate learning disability: a longitudinal analysis.

Substance use behaviors of young people attending a special school are reported over a 4-year period from the age of 12-16 years. The article investigated these behaviors by surveying a cohort of young people with a statement for moderate learning disabilities annually during the last 4 years of compulsory schooling. The findings show that these young people consistently reported lower levels of tobacco, alcohol, and cannabis use compared with those attending mainstream school. No other illicit drug use was reported. The potential implications of these findings are discussed in relation to the context and timing of targeted substance education and prevention initiatives for young people with moderate learning disability attending a special school.This resource was contributed by The National Documentation Centre on Drug Use.

Learning collaboration in General Internal Medicine: a pilot project for undergraduate students in nursing, physiotherapy and medicine

Background: A form of education called Interprofessional Education (IPE) occurs when two or more professions learn with, from and about each other. The purpose of IPE is to improve collaboration and the quality of care. Today, IPE is considered as a key educational approach for students in the health professions. IPE is highly effective when delivered in active patient care, such as in clinical placements. General internal medicine (GIM) is a core discipline where hospital-based clinical placements are mandatory for students in many health professions. However, few interprofessional (IP) clinical placements in GIM have been implemented. We designed such a placement. Placement design: The placement took place in the Department of Internal Medicine at the CHUV. It involved students from nursing, physiotherapy and medicine. The students were in their last year before graduation. Students formed teams consisting of one student from each profession. Each team worked in the same unit and had to take care of the same patient. The placement lasted three weeks. It included formal IP sessions, the most important being facilitated discussions or "briefings" (3x/w) during which the students discussed patient care and management. Four teams of students eventually took part in this project. Method: We performed a type of evaluation research called formative evaluation. This aimed at (1) understanding the educational experience and (2) assessing the impact of the placement on student learning. We collected quantitative data with pre-post clerkship questionnaires. We also collected qualitative data with two Focus Groups (FG) discussions at the end of the placement. The FG were audiotaped and transcribed. A thematic analysis was then performed. Results: We focused on the qualitative data, since the quantitative data lacked of statistical power due to the small numbers of students (N = 11). Five themes emerged from the FG analysis: (1) Learning of others' roles, (2) Learning collaborative competences, (3) Striking a balance between acquiring one's own professional competences and interprofessional competences, (4) Barriers to apply learnt IP competences in the future and (5) Advantages and disadvantages of IP briefings. Conclusions: Our IP clinical placement in GIM appeared to help students learn other professionals' roles and collaborative skills. Some challenges (e.g. finding the same patient for each team) were identified and will require adjustments.

Plataforma GNU/Linux : Servidor de Base de Dades

L'objectiu d'aquest projecte és aconseguir una distribució basada en el projecte Metadistros capaç d'arrencar des del CD. L'avantatge d'aquest tipus de distribucions és disposar de tot un sistema operatiu juntament amb tot un lot d'aplicacions sense necessitat d'instal·lar res al disc dur.