34 resultados para Virtual Performance


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Improving performance in sports requires a better understanding of the perception-action loop employed by athletes. Because of its inherent limitations, video playback doesn't permit this type of in-depth analysis. Interactive, immersive virtual reality can overcome these limitations and foster a better understanding of sports performance.

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The work ROTATING BRAINS / BEATING HEART was specifically developed for the opening performance of the 2010 DRHA conference. The conference’s theme ‘Sensual Technologies: Collaborative Practices of Interdisciplinarity explored collaborative relationships between the body and sensual/sensing technologies across various disciplines, looking to new approaches offered by various emerging fields and practices that incorporate new and existing technologies. The conference had a specific focus on SecondLife with roundtable events and discussions, led by performance artist Stelarc, as well as international participation via SecondLife.
The collaboration between Stelarc, the Avatar Orchestra Metaverse (AOM) and myself as the DRHA2010 conference program chair was a unique occurrence for this conference.

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This is a paper about resistance and affordance as they relate to music-making in the most extended sense, and perhaps about empathy if this is understood as a capacity to ‘read’ the resistances and affordances of objects, bodies, people and environments. It proceeds from a set of broad working assumptions which inform one individual’s musical practice, via a description a musical-instrument making project which is a hybrid of physical and virtual elements and is designed to test those assumptions, to a speculative finale in which it is suggested that musicking might, in some circumstances, be regarded in itself as a form of resistance. It moves from the intimate and personal, through what might be regarded as local concerns to more global observation, prefiguring the structure of the performance system it describes: the Virtual-Physical Feedback flute

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In order to use virtual reality as a sport analysis tool, we need to be sure that an immersed athlete reacts realistically in a virtual environment. This has been validated for a real handball goalkeeper facing a virtual thrower. However, we currently ignore which visual variables induce a realistic motor behavior of the immersed handball goalkeeper. In this study, we used virtual reality to dissociate the visual information related to the movements of the player from the visual information related to the trajectory of the ball. Thus, the aim is to evaluate the relative influence of these different visual information sources on the goalkeeper's motor behavior. We tested 10 handball goalkeepers who had to predict the final position of the virtual ball in the goal when facing the following: only the throwing action of the attacking player (TA condition), only the resulting ball trajectory (BA condition), and both the throwing action of the attacking player and the resulting ball trajectory (TB condition). Here we show that performance was better in the BA and TB conditions, but contrary to expectations, performance was substantially worse in the TA condition. A significant effect of ball landing zone does, however, suggest that the relative importance between visual information from the player and the ball depends on the targeted zone in the goal. In some cases, body-based cues embedded in the throwing actions may have a minor influence on the ball trajectory and vice versa. Kinematics analysis was then combined with these results to determine why such differences occur depending on the ball landing zone and consequently how it can clarify the role of different sources of visual information on the motor behavior of an athlete immersed in a virtual environment.

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Graphics Processing Units (GPUs) are becoming popular accelerators in modern High-Performance Computing (HPC) clusters. Installing GPUs on each node of the cluster is not efficient resulting in high costs and power consumption as well as underutilisation of the accelerator. The research reported in this paper is motivated towards the use of few physical GPUs by providing cluster nodes access to remote GPUs on-demand for a financial risk application. We hypothesise that sharing GPUs between several nodes, referred to as multi-tenancy, reduces the execution time and energy consumed by an application. Two data transfer modes between the CPU and the GPUs, namely concurrent and sequential, are explored. The key result from the experiments is that multi-tenancy with few physical GPUs using sequential data transfers lowers the execution time and the energy consumed, thereby improving the overall performance of the application.

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Presented is a study that expands the body of knowledge on the effect of in-cycle speed fluctuations on performance of small engines. It uses the methods developed previously by Callahan, et al. (1) to examine a variety of two-stroke engines and one four-stroke engine. The two-stroke engines were: a high performance single-cylinder, a low performance single-cylinder, a high performance multi-cylinder, and a medium performance multi-cylinder. The four-stroke engine was a high performance single-cylinder unit. Each engine was modeled in Virtual Engines, which is a fully detailed one-dimensional thermodynamic engine simulator. Measured or predicted in-cycle speed data were input into the engine models. Predicted performance changes due to drivetrain effects are shown in each case, and conclusions are drawn from those results. The simulations for the high performance single-cylinder two-stroke engine predicted significant in-cycle crankshaft speed fluctuation amplitudes and significant changes in performance when the fluctuations were input into the engine model. This was validated experimentally on a firing test engine based on a Yamaha YZ250. The four-stroke engine showed significant changes in predicted performance compared to the prediction with zero speed fluctuation assumed in the model. Measured speed fluctuations from a firing Yamaha YZ400F engine were applied to the simulation in addition to data from a simple free mass model. Both methods predicted similar fluctuation profiles and changes in performance. It is shown that the gear reduction between the crankshaft and clutch allowed for this similar behavior. The multi-cylinder, high performance two-stroke engine also showed significant changes in performance, in this case depending on the firing configuration. The low output two-stroke engine simulation showed only a negligible change in performance in spite of high amplitude speed fluctuations. This was due to its flat torque versus speed characteristic. The medium performance multi-cylinder two-stroke engine also showed only a negligible change in performance, in this case due to a relatively high inertia rotating assembly and multiple cylinder firing events within the revolution. These smoothed the net torque pulsations and reduced the amplitude of the speed fluctuation itself.

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BACKGROUND:
tissue MicroArrays (TMAs) are a valuable platform for tissue based translational research and the discovery of tissue biomarkers. The digitised TMA slides or TMA Virtual Slides, are ultra-large digital images, and can contain several hundred samples. The processing of such slides is time-consuming, bottlenecking a potentially high throughput platform.
METHODS:
a High Performance Computing (HPC) platform for the rapid analysis of TMA virtual slides is presented in this study. Using an HP high performance cluster and a centralised dynamic load balancing approach, the simultaneous analysis of multiple tissue-cores were established. This was evaluated on Non-Small Cell Lung Cancer TMAs for complex analysis of tissue pattern and immunohistochemical positivity.
RESULTS:
the automated processing of a single TMA virtual slide containing 230 patient samples can be significantly speeded up by a factor of circa 22, bringing the analysis time to one minute. Over 90 TMAs could also be analysed simultaneously, speeding up multiplex biomarker experiments enormously.
CONCLUSIONS:
the methodologies developed in this paper provide for the first time a genuine high throughput analysis platform for TMA biomarker discovery that will significantly enhance the reliability and speed for biomarker research. This will have widespread implications in translational tissue based research.