Adaptative study of closed and semi-closed noise barriers in a 3D ray tracing method
Closed barrier and semi-closed barrier are presented in the paper, the adaptive research is performed. Reducing effect of noise barrier with closed and semi-closed structure was studied by noise simulating program—RAYNOISE. The applied range of the closed and semi-closed noise barrier is confirmed. Simulating results showed that noise reduction of closed-shaped structure has good reducing effect at higher area of the shadow area. The noise reduction is 6dB(A) at the receiving point 22.2m height and 60m far behind the noise barrier, which is 1dB(A) higher than the semi-closed noise barrier. So it is suitable for higher receiving point. Semi-closed-shaped noise barrier has a good reducing noise effect at the area lower than 3m.
We present a methodology based on grammatical inference algorithms applied to the linguistic modeling of biological regulation networks. The linguistic approach to the problem of regulation networks was proposed by COLLADOVIDES, who proved and formalized the need for use of context sensitive languages to represent such networks. The learning of context sensitive languages is a difficult task, our proposed methodology describes this class from language with a simpler nature that can be learned by already consolidated grammars inference algorithms. In addition to the proposed methodology, we suggest promising directions for this research.