Particle-Based Fused Rendering

In this chapter, we propose a fused rendering technique that can integrally handle multiple irregular volumes. Although there is a strong requirement for understanding large-scale datasets generated from coupled simulation techniques such as computational structure mechanics (CSM) and computational fluid dynamics (CFD), there is no fused rendering technique to the best of our knowledge. For this purpose, we can employ the particle-based volume rendering (PBVR) technique for each irregular volume dataset. Since the current PBVR technique regards an irregular cell as a planar footprint during depth evaluation, the straightforward employment causes some artifacts especially at the cell boundaries. To solve the problem, we calculate the depth value based on the assumption that the opacity describes the cumulative distribution function (CDF) of a probability variable, w, which shows a length from the entry point in the fragment interval in the cell. In our experiments, we applied our method to numerical simulation results in which two different irregular grid cells are defined in the same space and confirmed its effectiveness with respect to the image quality

Angular-based Edge Bundled Parallel Coordinates Plot for the Visual Analysis of Large Ensemble Simulation Data

With the continuous increase in the computational power and resources of modern high-performance computing (HPC) systems, large-scale ensemble simulations have become widely used in various fields of science and engineering, and especially in meteorological and climate science. It is widely known that the simulation outputs are large time-varying, multivariate, and multivalued datasets which pose a particular challenge to the visualization and analysis tasks. In this work, we focused on the widely used Parallel Coordinates Plot (PCP) to analyze the interrelations between different parameters, such as variables, among the members. However, PCP may suffer from visual cluttering and drawing performance with the increase on the data size to be analyzed, that is, the number of polylines. To overcome this problem, we present an extension to the PCP by adding B\'{e}zier curves connecting the angular distribution plots representing the mean and variance of the inclination of the line segments between parallel axes. The proposed Angular-based Parallel Coordinates Plot (APCP) is capable of presenting a simplified overview of the entire ensemble data set while maintaining the correlation information between the adjacent variables. To verify its effectiveness, we developed a visual analytics prototype system and evaluated by using a meteorological ensemble simulation output from the supercomputer Fugaku

A Visual Analytics Approach for Hardware System Monitoring withStreaming Functional Data Analysis

Many real-world applications involve analyzing time-dependent phenomena, which are intrinsically functional, consisting of curves varying over a continuum (e.g., time). When analyzing continuous data, functional data analysis (FDA) provides substantial benefits, such as the ability to study the derivatives and to restrict the ordering of data. However, continuous data inherently has infinite dimensions, and for a long time series, FDA methods often suffer from high computational costs. The analysis problem becomes even more challenging when we must update the FDA results for continuously arriving data. In this paper, we present a visual analytics approach for monitoring and reviewing time series data streamed from a hardware system with a focus on identifying outliers by using FDA. To perform FDA while addressing the computational problem, we introduce new incremental and progressive algorithms that promptly generate the magnitude-shape (MS) plot, which conveys both the functional magnitude and shape outlyingness of time series data. In addition, by using an MS plot in conjunction with an FDA version of principal component analysis, we enhance the analyst's ability to investigate the visually-identified outliers. We illustrate the effectiveness of our approach with two use scenarios using real-world datasets. The resulting tool is evaluated by industry experts using real-world streaming datasets.Comment: 10 pages, 10 figure

PetaFlow: a global computing-networking-visualisation unitwith social impact

International audienceThe PetaFlow application aims to contribute to the use of high performance computational resources forthe benefit of society. To this goal the emergence of adequate information and communication technologies withrespect to high performance computing-networking-visualisation and their mutual awareness is required. Thedeveloped technology and algorithms are presented and applied to a real global peta-scale data intensive scientificproblem with social and medical importance, i.e. human upper airflow modelling

High-Resolution Imaging of the Retinal Nerve Fiber Layer in Normal Eyes Using Adaptive Optics Scanning Laser Ophthalmoscopy

To conduct high-resolution imaging of the retinal nerve fiber layer (RNFL) in normal eyes using adaptive optics scanning laser ophthalmoscopy (AO-SLO).AO-SLO images were obtained in 20 normal eyes at multiple locations in the posterior polar area and a circular path with a 3-4-mm diameter around the optic disc. For each eye, images focused on the RNFL were recorded and a montage of AO-SLO images was created.AO-SLO images for all eyes showed many hyperreflective bundles in the RNFL. Hyperreflective bundles above or below the fovea were seen in an arch from the temporal periphery on either side of a horizontal dividing line to the optic disc. The dark lines among the hyperreflective bundles were narrower around the optic disc compared with those in the temporal raphe. The hyperreflective bundles corresponded with the direction of the striations on SLO red-free images. The resolution and contrast of the bundles were much higher in AO-SLO images than in red-free fundus photography or SLO red-free images. The mean hyperreflective bundle width around the optic disc had a double-humped shape; the bundles at the temporal and nasal sides of the optic disc were narrower than those above and below the optic disc (P<0.001). RNFL thickness obtained by optical coherence tomography correlated with the hyperreflective bundle widths on AO-SLO (P<0.001)AO-SLO revealed hyperreflective bundles and dark lines in the RNFL, believed to be retinal nerve fiber bundles and Müller cell septa. The widths of the nerve fiber bundles appear to be proportional to the RNFL thickness at equivalent distances from the optic disc

4D street view: a video-based visualization method

We propose a new visualization method for massive supercomputer simulations. The key idea is to scatter multiple omnidirectional cameras to record the simulation via in situ visualization. After the simulations are complete, researchers can interactively explore the data collection of the recorded videos by navigating along a path in four-dimensional spacetime. We demonstrate the feasibility of this method by applying it to three different fluid and magnetohydrodynamics simulations using up to 1,000 omnidirectional cameras

Fusion visualization for fluid dynamics in blood vessel

The speed up of supercomputers has increased the complexity of simulations. To analyze such kind of data, new types of visualization software are needed. As one of approach for meeting this requirement, we are developing the “Fusion Visualization” in a project sponsored by the Japan Science and Technology Agency (JST). It can execute fused visualization of simulation data combining both volume and surface rendering. The overall concept was reported last year at the AROB 18th International Symposium in Korea. In this work, we are reporting the ongoing research with an application example related to blood flow simulation

High-quality particle-based volume rendering for large-scale unstructured volume datasets

In this article, we propose a technique for improving the image quality of particle-based volume rendering (PBVR). A large-scale unstructured volume dataset often contains multiple sub-volumes, which cannot be ordered by visibility. PBVR can handle this type of volume dataset. Sampling misses often occur when the transfer function undergoes drastic changes, which can result in poor image quality. To reduce sampling misses caused by the high-frequency transfer function, we develop a new sampling technique called “layered sampling”. To confirm the effectiveness of our technique, we apply the proposed technique to a large-scale unstructured volume dataset subdivided into multiple sub-volumes