Sentence examples for generation of visualization from inspiring English sources

The future generation of visualization tools should aim to reduce the gap between analysis and visualization.

Ideally, the next generation of visualization tools should be able to present very heterogeneous data coming from databases, experiments and text-mining applications.

In addition, the extension of layout algorithms to encompass a third dimension would be one central step towards a new generation of visualization tools.

Finally, we will highlight crucial gaps in the landscape of data visualization, discuss how existing tools could be improved to fill these gaps and lay out the perspectives and goals for the next generation of visualization tools.

Before this new generation of visualization tools became available Otter [ 60], Plankton [ 61], GraphViz, Tulip[ 11], Negopy[ 62], KrackPlot [ 63], and MultiNet [ 64], have been the tools of choice.

Yet, results of large-scale systems biology experiments frequently exceed hundred thousands of data points today, and many existing visualization tools are not able to cope with these demands calling for a new generation of visualization tools.

Learning advantages for the generation of visualizations could be attributed to learners' translating across modalities, from a verbal format into a visual format.

Visualization instrument is a new generation of information visualization techniques that is adapted to multivariate, time-sharing, and dynamic complex network analysis.

Among them, the CiteSpace series application software based on Java platform developed by Professor Chaomei Chen from Dexrel University in the USA is a new generation of information visualization technology, which is suitable for multiple, dynamic, and complex network analysis and has become a new method of scientific metrology [25].

The implementation of the developed algorithm allows the generation and visualization of the densest possible and loose-packing arrangements of aggregates.

However, due to the overhead of handling complex geometries, mesh generation and visualization of results, algorithm developers often tend to consider only simple test models in simple geometries, often restricted to one or two spatial dimensions.