5 resultados para Activity recognition
em CiencIPCA - Instituto Politécnico do Cávado e do Ave, Portugal
Resumo:
Emotions play a central role in our daily lives, influencing the way we think and act, our health and sense of well-being, and films are by excellence the form of art that exploits our affective, perceptual and intellectual activity, holding the potential for a significant impact. Video is becoming a dominant and pervasive medium, and online video a growing entertainment activity on the web and iTV, mainly due to technological developments and the trends for media convergence. In addition, the improvement of new techniques for gathering emotional information about videos, both through content analysis or user implicit feedback through user physiological signals complemented in manual labeling from users, is revealing new ways for exploring emotional information in videos, films or TV series, and brings out new perspectives to enrich and personalize video access. In this work, we reflect on the power that emotions have in our lives, on the emotional impact of movies, and on how to address this emotional dimension in the way we classify and access movies, by exploring and evaluating the design of iFelt in its different ways to classify, access, browse and visualize movies based on their emotional impac
Resumo:
La presente comunicación tiene como objetivo analizar la complementariedad y la posibilidad de integración entre las herramientas de gestión Cuadro de Mando Integral (CMI), Activity Based Costing (ABC) y Activity Based management (ABM). Para la realización del estudio empírico hemos recurrido a los datos obtenidos mediante la aplicación de un cuestionario postal a 591 organizaciones públicas (ayuntamientos, hospitales, empresas municipales y empresas intermunicipales) y 549 organizaciones privadas (grandes empresas y pequeñas y medianas empresas) portuguesas, con una tasa de respuesta total del 31,3%. Los resultados obtenidos indican que, contrariamente al registrado en las organizaciones públicas, observamos que un número significativo de organizaciones privadas ya utilizaba los sistemas ABC/ABM antes del CMI y que los han integrado (total o parcialmente) o esperan integrar en el CMI.
Resumo:
Exposure to a novel environment triggers the response of several brain areas that regulate emotional behaviors. Here, we studied theta oscillations within the hippocampus (HPC)-amygdala (AMY)-medial prefrontal cortex (mPFC) network in exploration of a novel environment and subsequent familiarization through repeated exposures to that same environment; in addition, we assessed how concomitant stress exposure could disrupt this activity and impair both behavioral processes. Local field potentials were simultaneously recorded from dorsal and ventral hippocampus (dHPC and vHPC respectively), basolateral amygdala (BLA) and mPFC in freely behaving rats while they were exposed to a novel environment, then repeatedly re-exposed over the course of 3 weeks to that same environment and, finally, on re-exposure to a novel unfamiliar environment. A longitudinal analysis of theta activity within this circuit revealed a reduction of vHPC and BLA theta power and vHPC-BLA theta coherence through familiarization which was correlated with a return to normal exploratory behavior in control rats. In contrast, a persistent over-activation of the same brain regions was observed in stressed rats that displayed impairments in novel exploration and familiarization processes. Importantly, we show that stress also affected intra-hippocampal synchrony and heightened the coherence between vHPC and BLA. In summary, we demonstrate that modulatory theta activity in the aforementioned circuit, namely in the vHPC and BLA, is correlated with the expression of anxiety in novelty-induced exploration and familiarization in both normal and pathological conditions.
Resumo:
Este artículo tiene como objetivo analizar la complementariedad y la posibilidad de integración entre las herramientas de gestión Cuadro de Mando Integral (CMI), Activity Based Costing (ABC) y Activity Based management (ABM). Para la realización del estudio empírico hemos recurrido a los datos obtenidos mediante la aplicación de un cuestionario postal a 591 organizaciones públicas (ayuntamientos, hospitales, empresas municipales y empresas intermunicipales) y 549 organizaciones privadas (grandes empresas y pequeñas y medianas empresas) portuguesas, con una tasa de respuesta total del 31,3%. Los resultados obtenidos indican que, contrariamente al registrado en las organizaciones públicas, observamos que un número significativo de organizaciones privadas ya utilizaba los sistemas ABC/ABM antes del CMI y que los han integrado (total o parcialmente) o esperan integrar en el CMI.
Resumo:
Dental implant recognition in patients without available records is a time-consuming and not straightforward task. The traditional method is a complete user-dependent process, where the expert compares a 2D X-ray image of the dental implant with a generic database. Due to the high number of implants available and the similarity between them, automatic/semi-automatic frameworks to aide implant model detection are essential. In this study, a novel computer-aided framework for dental implant recognition is suggested. The proposed method relies on image processing concepts, namely: (i) a segmentation strategy for semi-automatic implant delineation; and (ii) a machine learning approach for implant model recognition. Although the segmentation technique is the main focus of the current study, preliminary details of the machine learning approach are also reported. Two different scenarios are used to validate the framework: (1) comparison of the semi-automatic contours against implant’s manual contours of 125 X-ray images; and (2) classification of 11 known implants using a large reference database of 601 implants. Regarding experiment 1, 0.97±0.01, 2.24±0.85 pixels and 11.12±6 pixels of dice metric, mean absolute distance and Hausdorff distance were obtained, respectively. In experiment 2, 91% of the implants were successfully recognized while reducing the reference database to 5% of its original size. Overall, the segmentation technique achieved accurate implant contours. Although the preliminary classification results prove the concept of the current work, more features and an extended database should be used in a future work.