1,721,039 research outputs found

    Design and implementation of a VR environment aimed at enhancing the Social Anxiety Disorder’s (SAD) treatment. Evaluation of the sense of presence and immersion

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    Background and aim: We present here a novel approach to Virtual Reality Treatment (VRET) of Social Anxiety Disorders. It is based on a VR ecological scenario (that of a school room with desks) that can be personalized according to the actual fear level of the patient, adjusting the number of schoolmates that can be present together inside the room and the distance between the desks. Methods: We then conducted a user study to explore the sense of presence (Presence Questionnaire, PQ), immersive tendencies (Immersive Tendencies Questionnaire, ITQ), and subjective mental workload (NASA Task Load Index, TLX). The study evaluated 34 healthy students (average age: 24.558 years), of which 18 females. Results: Results from a us-ability trial are extremely positive. Our data suggests that participants mostly liked the high realism and sense of immersion of the Virtual Environment and the possibility to explore it widely. On the other side, the amount of workload of the task was evaluated very low, and therefore users can concentrate on the task. Conclusions: We conclude the article by discussing possible future directions for a large-scale pilot, that can lead to a solution that can be used at home to train under the guide and periodic supervision of a therapist (www.actabiomedica.it

    Robot exploration of indoor environments using incomplete and inaccurate prior knowledge

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    Exploration is a task in which autonomous mobile robots incrementally discover features of interest in initially unknown environments. We consider the problem of exploration for map building, in which a robot explores an indoor environment in order to build a metric map. Most of the current exploration strategies used to select the next best locations to visit ignore prior knowledge about the environments to explore that, in some practical cases, could be available. In this paper, we present an exploration strategy that evaluates the amount of new areas that can be perceived from a location according to a priori knowledge about the structure of the indoor environment being explored, like the floor plan or the contour of external walls. Although this knowledge can be incomplete and inaccurate (e.g., a floor plan typically does not represent furniture and objects and consequently may not fully mirror the structure of the real environment), we experimentally show, both in simulation and with real robots, that employing prior knowledge improves the exploration performance in a wide range of settings

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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