4,906 research outputs found

    Exploration of Reaction Pathways and Chemical Transformation Networks

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    For the investigation of chemical reaction networks, the identification of all relevant intermediates and elementary reactions is mandatory. Many algorithmic approaches exist that perform explorations efficiently and automatedly. These approaches differ in their application range, the level of completeness of the exploration, as well as the amount of heuristics and human intervention required. Here, we describe and compare the different approaches based on these criteria. Future directions leveraging the strengths of chemical heuristics, human interaction, and physical rigor are discussed.Comment: 48 pages, 4 figure

    Prop-Based Haptic Interaction with Co-location and Immersion: an Automotive Application

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    Most research on 3D user interfaces aims at providing only a single sensory modality. One challenge is to integrate several sensory modalities into a seamless system while preserving each modality's immersion and performance factors. This paper concerns manipulation tasks and proposes a visuo-haptic system integrating immersive visualization, tactile force and tactile feedback with co-location. An industrial application is presented

    Novel Multimodal Feedback Techniques for In-Car Mid-Air Gesture Interaction

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    This paper presents an investigation into the effects of different feedback modalities on mid-air gesture interaction for infotainment systems in cars. Car crashes and near-crash events are most commonly caused by driver distraction. Mid-air interaction is a way of reducing driver distraction by reducing visual demand from infotainment. Despite a range of available modalities, feedback in mid-air gesture systems is generally provided through visual displays. We conducted a simulated driving study to investigate how different types of multimodal feedback can support in-air gestures. The effects of different feedback modalities on eye gaze behaviour, and the driving and gesturing tasks are considered. We found that feedback modality influenced gesturing behaviour. However, drivers corrected falsely executed gestures more often in non-visual conditions. Our findings show that non-visual feedback can reduce visual distraction significantl

    Using virtual reality and 3D industrial numerical models for immersive interactive checklists

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    At the different stages of the PLM, companies develop numerous checklist-based procedures involving prototype inspection and testing. Besides, techniques from CAD, 3D imaging, animation and virtual reality now form a mature set of tools for industrial applications. The work presented in this article develops a unique framework for immersive checklist-based project reviews that applies to all steps of the PLM. It combines immersive navigation in the checklist, virtual experiments when needed and multimedia update of the checklist. It provides a generic tool, independent of the considered checklist, relies on the integration of various VR tools and concepts, in a modular way, and uses an original gesture recognition. Feasibility experiments are presented, validating the benefits of the approach

    An Overview of Self-Adaptive Technologies Within Virtual Reality Training

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    This overview presents the current state-of-the-art of self-adaptive technologies within virtual reality (VR) training. Virtual reality training and assessment is increasingly used for five key areas: medical, industrial & commercial training, serious games, rehabilitation and remote training such as Massive Open Online Courses (MOOCs). Adaptation can be applied to five core technologies of VR including haptic devices, stereo graphics, adaptive content, assessment and autonomous agents. Automation of VR training can contribute to automation of actual procedures including remote and robotic assisted surgery which reduces injury and improves accuracy of the procedure. Automated haptic interaction can enable tele-presence and virtual artefact tactile interaction from either remote or simulated environments. Automation, machine learning and data driven features play an important role in providing trainee-specific individual adaptive training content. Data from trainee assessment can form an input to autonomous systems for customised training and automated difficulty levels to match individual requirements. Self-adaptive technology has been developed previously within individual technologies of VR training. One of the conclusions of this research is that while it does not exist, an enhanced portable framework is needed and it would be beneficial to combine automation of core technologies, producing a reusable automation framework for VR training
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