top of page

専門職グループ

公開·49名のメンバー

Autocad Raster Design 2014 Serial 24



Strong motion recordings are the key in many earthquake engineering applications and are also fundamental for seismic design. The present study focuses on the automated correction of accelerograms, analog and digital. The main feature of the proposed algorithm is the automatic selection for the cut-off frequencies based on a minimum spectral value in a predefined frequency bandwidth, instead of the typical signal-to-noise approach. The algorithm follows the basic steps of the correction procedure (instrument correction, baseline correction and appropriate filtering). Besides the corrected time histories, Peak Ground Acceleration, Peak Ground Velocity, Peak Ground Displacement values and the corrected Fourier Spectra are also calculated as well as the response spectra. The algorithm is written in Matlab environment, is fast enough and can be used for batch processing or in real-time applications. In addition, the possibility to also perform a signal-to-noise ratio is added as well as to perform causal or acausal filtering. The algorithm has been tested in six significant earthquakes (Kozani-Grevena 1995, Aigio 1995, Athens 1999, Lefkada 2003 and Kefalonia 2014) of the Greek territory with analog and digital accelerograms.




autocad raster design 2014 serial 24



The geometry of anatomical specimens is very complex and accurate 3D reconstruction is important for morphological studies, finite element analysis (FEA) and rapid prototyping. Although magnetic resonance imaging, computed tomography and laser scanners can be used for reconstructing biological structures, the cost of the equipment is fairly high and specialised technicians are required to operate the equipment, making such approaches limiting in terms of accessibility. In this paper, a novel automatic system for 3D surface reconstruction of the chick eye from digital photographs of a serially sectioned specimen is presented as a potential cost-effective and practical alternative. The system is designed to allow for automatic detection of the external surface of the chick eye. Automatic alignment of the photographs is performed using a combination of coloured markers and an algorithm based on complex phase order likelihood that is robust to noise and illumination variations. Automatic segmentation of the external boundaries of the eye from the aligned photographs is performed using a novel level-set segmentation approach based on a complex phase order energy functional. The extracted boundaries are sampled to construct a 3D point cloud, and a combination of Delaunay triangulation and subdivision surfaces is employed to construct the final triangular mesh. Experimental results using digital photographs of the chick eye show that the proposed system is capable of producing accurate 3D reconstructions of the external surface of the eye. The 3D model geometry is similar to a real chick eye and could be used for morphological studies and FEA.


グループについて

グループへようこそ!他のメンバーと交流したり、最新情報をチェックしたり、動画をシェアすることもできます。
bottom of page