Visualization of residents in long-term care centres through mobile natural user interfaces (NUI)

Arunachalan, Bhuvaneswari; Diamond, Sara; Stevens, Anne; Talaie, Borzu; Ghaderi, Maziar

doi:10.1109/ldav.2013.6675175

2013 IEEE Symposium on Large-Scale Data Analysis and Visualization (LDAV) 2013

DOI: 10.1109/ldav.2013.6675175

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Visualization of residents in long-term care centres through mobile natural user interfaces (NUI)

Bhuvaneswari Arunachalan

Sara Diamond

Anne Stevens

et al.

Abstract: Open Res ear c h is a publicly acces si bl e, curat e d repositor y for the pres e r v a ti on and diss e m i n a ti o n of scholarly and creativ e outp u t of the OCAD Univer sity com m u n i t y. Mat erial in Open Res earc h is open acces s and mad e available via the cons e n t of the author and/or rights holder on a non-exclusiv e basis.

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2023

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Real-Time Interactive Parallel Visualization of Large-Scale Flow-Field Data

Chen

et al. 2023

Applied Sciences

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With the increasing demand for high precision in numerical simulations using computational fluid dynamics (CFD), the use of large-scale grids for discretized solutions has become a trend, resulting in an explosive growth of flow-field data size. To address the challenges posed by large-scale flow-field data for real-time interactive visualization, this paper proposes novel strategies for data partitioning and communication management. Firstly, we propose a data-partitioning strategy based on grid segmentation. This approach constructs metadata to create file viewports for each process and performs grid partitioning. Subsequently, it reconstructs sub-grids within each process and utilizes a coordinate-mapping algorithm to map global coordinates to local process coordinates, facilitating access to attribute variables through a lookup table. Secondly, we introduce a real-time interactive method for large-scale flow fields. This method leverages the system architecture of high-speed interconnection among compute nodes in a cluster environment and low-speed interconnection between service nodes and rendering nodes. It enables coordinated management of parallel rendering and synchronized rendering methods. The experimental results on typical flow-field data demonstrate that the proposed data-partitioning strategy improves the loading speed of millions of grid-level data by a factor of 7, surpassing ParaView’s performance by 1.5 times. Furthermore, it achieves system load balancing. Real-time interaction experiments with datasets containing 500 million and 800 million grid cells exhibit millisecond-level latencies, demonstrating the effectiveness of the proposed communication management method in meeting the real-time interactive visualization demands of large-scale flow-field data.

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Real-Time Interactive Parallel Visualization of Large-Scale Flow-Field Data

Chen

et al. 2023

Applied Sciences

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Visualization of residents in long-term care centres through mobile natural user interfaces (NUI)

Cited by 1 publication

References 7 publications

Real-Time Interactive Parallel Visualization of Large-Scale Flow-Field Data

Real-Time Interactive Parallel Visualization of Large-Scale Flow-Field Data

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