110 resultados para Emotional process


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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.

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La importància de la intel.ligència emocional en una època de canvi. Valors i sentiments com a font i garantia d'autonomia i felicitat personal i social dins del marc d'una societat consumista i ultratecnificada en procés de canvi.

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Construcció d'una aplicació web a partir de les especificacions d'un client imaginari. Estudi i utilització del mètode Rational Unified Process, el més habitual actualment en la construcció de software. Disseny d'una base de dades i implementació del model lògic mitjançant un SGBD punter al mercat com Oracle.

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Personalization in e-learning allows the adaptation of contents, learning strategiesand educational resources to the competencies, previous knowledge or preferences of the student. This project takes a multidisciplinary perspective for devising standards-based personalization capabilities into virtual e-learning environments, focusing on the conceptof adaptive learning itinerary, using reusable learning objects as the basis of the system and using ontologies and semantic web technologies.

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Supervisory systems evolution makes the obtaining of significant information from processes more important in the way that the supervision systems' particular tasks are simplified. So, having signal treatment tools capable of obtaining elaborate information from the process data is important. In this paper, a tool that obtains qualitative data about the trends and oscillation of signals is presented. An application of this tool is presented as well. In this case, the tool, implemented in a computer-aided control systems design (CACSD) environment, is used in order to give to an expert system for fault detection in a laboratory plant

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Emotions are crucial for user's decision making in recommendation processes. We first introduce ambient recommender systems, which arise from the analysis of new trends on the exploitation of the emotional context in the next generation of recommender systems. We then explain some results of these new trends in real-world applications through the smart prediction assistant (SPA) platform in an intelligent learning guide with more than three million users. While most approaches to recommending have focused on algorithm performance. SPA makes recommendations to users on the basis of emotional information acquired in an incremental way. This article provides a cross-disciplinary perspective to achieve this goal in such recommender systems through a SPA platform. The methodology applied in SPA is the result of a bunch of technology transfer projects for large real-world rccommender systems

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En el context de la crisi econòmica i social que vivien els Estats Units a començament dels anys trenta, diversos actors polítics i socials van elaborar missatges que provaven d’acarar els ciutadans amb la realitat, però sobretot de restituir-los la confiança en ells mateixos i en el país. Aquest article analitza els discursos i les aportacions ideològiques de dues de les personalitats més destacades que participaren en aquest procés de reconstrucció emocional: el president Franklin D. Roosevelt i el cineasta Frank Capra. El text cerca d’establir les connexions entre aquests dos discursos, descobrir-ne les coincidències i, també, les diferències, i plantejar una aproximació al cinema com un mitjà de comunicació que va més enllà del simple entreteniment, per a convertir-se, en diverses ocasions, en un eficaç document amb el qual apropar-se a una època, desxifrar-ne els aspectes més significatius

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This paper introduces how artificial intelligence technologies can be integrated into a known computer aided control system design (CACSD) framework, Matlab/Simulink, using an object oriented approach. The aim is to build a framework to aid supervisory systems analysis, design and implementation. The idea is to take advantage of an existing CACSD framework, Matlab/Simulink, so that engineers can proceed: first to design a control system, and then to design a straightforward supervisory system of the control system in the same framework. Thus, expert systems and qualitative reasoning tools are incorporated into this popular CACSD framework to develop a computer aided supervisory system design (CASSD) framework. Object-variables an introduced into Matlab/Simulink for sharing information between tools

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Report for the scientific sojourn carried out at the University Medical Center, Swiss, from 2010 to 2012. Abundant evidence suggests that negative emotional stimuli are prioritized in the perceptual systems, eliciting enhanced neural responses in early sensory regions as compared with neutral information. This facilitated detection is generally paralleled by larger neural responses in early sensory areas, relative to the processing of neutral information. In this sense, the amygdala and other limbic regions, such as the orbitofrontal cortex, may play a critical role by sending modulatory projections onto the sensory cortices via direct or indirect feedback.The present project aimed at investigating two important issues regarding these mechanisms of emotional attention, by means of functional magnetic resonance imaging. In Study I, we examined the modulatory effects of visual emotion signals on the processing of task-irrelevant visual, auditory, and somatosensory input, that is, the intramodal and crossmodal effects of emotional attention. We observed that brain responses to auditory and tactile stimulation were enhanced during the processing of visual emotional stimuli, as compared to neutral, in bilateral primary auditory and somatosensory cortices, respectively. However, brain responses to visual task-irrelevant stimulation were diminished in left primary and secondary visual cortices in the same conditions. The results also suggested the existence of a multimodal network associated with emotional attention, presumably involving mediofrontal, temporal and orbitofrontal regions Finally, Study II examined the different brain responses along the low-level visual pathways and limbic regions, as a function of the number of retinal spikes during visual emotional processing. The experiment used stimuli resulting from an algorithm that simulates how the visual system perceives a visual input after a given number of retinal spikes. The results validated the visual model in human subjects and suggested differential emotional responses in the amygdala and visual regions as a function of spike-levels. A list of publications resulting from work in the host laboratory is included in the report.

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Report for the scientific sojourn carried out at the University Medical Center, Swiss, from 2010 to 2012. Abundant evidence suggests that negative emotional stimuli are prioritized in the perceptual systems, eliciting enhanced neural responses in early sensory regions as compared with neutral information. This facilitated detection is generally paralleled by larger neural responses in early sensory areas, relative to the processing of neutral information. In this sense, the amygdala and other limbic regions, such as the orbitofrontal cortex, may play a critical role by sending modulatory projections onto the sensory cortices via direct or indirect feedback.The present project aimed at investigating two important issues regarding these mechanisms of emotional attention, by means of functional magnetic resonance imaging. In Study I, we examined the modulatory effects of visual emotion signals on the processing of task-irrelevant visual, auditory, and somatosensory input, that is, the intramodal and crossmodal effects of emotional attention. We observed that brain responses to auditory and tactile stimulation were enhanced during the processing of visual emotional stimuli, as compared to neutral, in bilateral primary auditory and somatosensory cortices, respectively. However, brain responses to visual task-irrelevant stimulation were diminished in left primary and secondary visual cortices in the same conditions. The results also suggested the existence of a multimodal network associated with emotional attention, presumably involving mediofrontal, temporal and orbitofrontal regions Finally, Study II examined the different brain responses along the low-level visual pathways and limbic regions, as a function of the number of retinal spikes during visual emotional processing. The experiment used stimuli resulting from an algorithm that simulates how the visual system perceives a visual input after a given number of retinal spikes. The results validated the visual model in human subjects and suggested differential emotional responses in the amygdala and visual regions as a function of spike-levels. A list of publications resulting from work in the host laboratory is included in the report.

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This paper analyzes and evaluates, in the context of Ontology learning, some techniques to identify and extract candidate terms to classes of a taxonomy. Besides, this work points out some inconsistencies that may be occurring in the preprocessing of text corpus, and proposes techniques to obtain good terms candidate to classes of a taxonomy.