933 resultados para Large Scale Virtual Environments


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In this dissertation, the problem of creating effective large scale Adaptive Optics (AO) systems control algorithms for the new generation of giant optical telescopes is addressed. The effectiveness of AO control algorithms is evaluated in several respects, such as computational complexity, compensation error rejection and robustness, i.e. reasonable insensitivity to the system imperfections. The results of this research are summarized as follows: 1. Robustness study of Sparse Minimum Variance Pseudo Open Loop Controller (POLC) for multi-conjugate adaptive optics (MCAO). The AO system model that accounts for various system errors has been developed and applied to check the stability and performance of the POLC algorithm, which is one of the most promising approaches for the future AO systems control. It has been shown through numerous simulations that, despite the initial assumption that the exact system knowledge is necessary for the POLC algorithm to work, it is highly robust against various system errors. 2. Predictive Kalman Filter (KF) and Minimum Variance (MV) control algorithms for MCAO. The limiting performance of the non-dynamic Minimum Variance and dynamic KF-based phase estimation algorithms for MCAO has been evaluated by doing Monte-Carlo simulations. The validity of simple near-Markov autoregressive phase dynamics model has been tested and its adequate ability to predict the turbulence phase has been demonstrated both for single- and multiconjugate AO. It has also been shown that there is no performance improvement gained from the use of the more complicated KF approach in comparison to the much simpler MV algorithm in the case of MCAO. 3. Sparse predictive Minimum Variance control algorithm for MCAO. The temporal prediction stage has been added to the non-dynamic MV control algorithm in such a way that no additional computational burden is introduced. It has been confirmed through simulations that the use of phase prediction makes it possible to significantly reduce the system sampling rate and thus overall computational complexity while both maintaining the system stable and effectively compensating for the measurement and control latencies.

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In 2003, a large landslide occurred along the Ontonagon River, located in the Upper Peninsula of Michigan, and adjacent to US-45 in Ontonagon County. The failure took place during the springtime, when the river reached a peak discharge that was the second highest on record. The volume of the slide has been estimated to be approximately 1,400,000 cubic yards. The colluvium blocked the river, forcing a new channel to be carved around the debris. The landslide consisted of a silt layer at its base, overlain by a coarsening upward sand sequence, and finally a varved glacio-lacustrine clay with sparse dropstone inclusions making up the upper section of hillside.

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The grasping of virtual objects has been an active research field for several years. Solutions providing realistic grasping rely on special hardware or require time-consuming parameterizations. Therefore, we introduce a flexible grasping algorithm enabling grasping without computational complex physics. Objects can be grasped and manipulated with multiple fingers. In addition, multiple objects can be manipulated simultaneously with our approach. Through the usage of contact sensors the technique is easily configurable and versatile enough to be used in different scenarios.

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This article begins with some recent considerations about real-time music, inspired by the latest contribution of French composer Philippe Manoury. Then, through the case study of the scenic performance La Traversée de la nuit, we analyse some perspectives for designing an Informed Virtual Environment dedicated to live show artistic domain.

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Quality of education should be stable or permanently increased – even if the number of students rises. Quality of education is often related to possibilities for active learning and individual facilitation. This paper deals with the question how high-quality learning within oversized courses could be enabled and it presents the approach of e-flashcards that enables active learning and individual facilitation within large scale university courses.

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The characteristics of moving sound sources have strong implications on the listener's distance perception and the estimation of velocity. Modifications of the typical sound emissions as they are currently occurring due to the tendency towards electromobility have an impact on the pedestrian's safety in road traffic. Thus, investigations of the relevant cues for velocity and distance perception of moving sound sources are not only of interest for the psychoacoustic community, but also for several applications, like e.g. virtual reality, noise pollution and safety aspects of road traffic. This article describes a series of psychoacoustic experiments in this field. Dichotic and diotic stimuli of a set of real-life recordings taken from a passing passenger car and a motorcycle were presented to test subjects who in turn were asked to determine the velocity of the object and its minimal distance from the listener. The results of these psychoacoustic experiments show that the estimated velocity is strongly linked to the object's distance. Furthermore, it could be shown that binaural cues contribute significantly to the perception of velocity. In a further experiment, it was shown that - independently of the type of the vehicle - the main parameter for distance determination is the maximum sound pressure level at the listener's position. The article suggests a system architecture for the adequate consideration of moving sound sources in virtual auditory environments. Virtual environments can thus be used to investigate the influence of new vehicle powertrain concepts and the related sound emissions of these vehicles on the pedestrians' ability to estimate the distance and velocity of moving objects.