Understanding the structure and evolution of spatial-temporal networks is crucial for different fields ranging from urbanism to epidemiology. As location based technologies are pervasively used in our daily life, large amount of sensing data has brought the opportunities to study human activities and city dynamics. Ubiquitous cell phones can be such a sensor to analyze the social connection and boundaries of geographical regions. In this paper, we exploit user mobility based on large-scale mobile phone records to study urban areas. We collect the call data records from 1 million anonymous subscribers of 8 weeks and study the user mobility flux between different regions. First we construct the urban areas as a spatial network and use modularity detection algorithm to study the intrinsic connection between map areas. Second, another generative model which is widely used in linguistic context is adopted to explore the functions of regions. Based on mobile call records we are able to derive the partitions which match boundaries of the administrative districts. Our results can also catch the dynamics of urban area as the basis for city planning and policy making.

In this paper, a three part algorithm is employed to obtain stable convergence during stress dependent oxidation simulation using the finite element method is presented. By introducing (1) a reduced integration formulation, (2) an averaging procedure for the mid-side node velocities at the Si/SiO2 interface, and (3) a three-node element to discretize the oxidant diffusion equation, major improvements in achieving stable convergence are realized during stress dependent oxidation simulation. This technique is generally applicable for an oxidation simulator using the finite element method.