Motivated by the prevalent data science applications of processing large-scale graph data such as social networks and biological networks, this paper investigates lossless compression of data in the ...

Learn what a force-directed layout is, how it works, and what are its advantages and disadvantages for visualizing network data with graph theory and algorithms. Agree & Join LinkedIn ...

Wedgelet representations of graph signals can be encoded in a simple way by a set of graph nodes and applied easily to the compression of graph signals and images. A detailed description of the ...

The deep learning neural network has been used to compress, reorganize, and save images and data of different sizes. However, it has several problems, the most important of which is that it takes a ...

The force bounds are calculated by finding the corresponding force to the inclination point. A 0.5% margin is used to define the flatness of the graph. The intersection between these bounds and the ...

Compression to EF. For the above formulation, a series of tablets was compressed at a constant force of 650 daN with a nominal tablet weight of 233 mg. Tablets were compressed within ± 4% of their ...

Purpose To evaluate the compression characteristics of the human lens nucleocortex in relation to its LOCSIII clinical grading. Methods Sixteen subjects undergoing planned extracapsular cataract ...

Motivated by the prevalent data science applications of processing and mining large-scale graph data such as social networks, web graphs, and biological networks, as well as the high I/O and ...