Lossless data compression scheme based on neural network and SVM

First, the compression-awaited data are regarded Lis character strings which are produced by virtual information source mapping M. then the model of the virtual information source M is established by neural network and SVM. Last we construct a lossless data compression (coding) scheme based oil neural network and SVM with the model, an integer function and a SVM discriminant. The scheme differs from the old entropy coding (compressions) inwardly, and it can compress some data compressed by the old entropy coding.

Strings of interconnected hollow carbon nanoparticles with porous shells prepared using simple solid-phase synthesis

Strings of interconnected hollow carbon nanoparticles with porous shells were prepared by simple heat-treatments of a mixture of resorcinol-formaldehyde gel and transition-metal salts. The sample was characterized by scanning electron microscopy, transmission electron microscopy, X-ray diffraction and nitrogen adsorption. Results show that the sample consisted of relatively uniform hollow particles with sizes ranging from 70 to 80 nm forming a strings-of-pearls-like nanostructure. The material with porous shells possessed well-developed graphitic structure with an interlayer (d(002)) spacing of 0.3369 nm and the stack height of the graphite crystallites of 9 nm.