Publications (6)
Impact of Wind Direction on Flow and Turbulent Statistics Over a Realistic Urban Area: A Large-Eddy Simulation Study
Josep M. Duró, Ernest Mestres, Ming Teng +2
Effects of wind direction in realistic urban canopies remain difficult to characterize systematically because local flow patterns, building-height variability, and turbulent statis…
Bayesian Analysis of fMRI data with Spatially-Varying Autoregressive Orders
Ming Teng, Farouk S. Nathoo, Timothy D. Johnson
Statistical modeling of fMRI data is challenging as the data are both spatially and temporally correlated. Spatially, measurements are taken at thousands of contiguous regions, cal…
Time Series Analysis of fMRI Data: Spatial Modelling and Bayesian Computation
Ming Teng, Timothy Johnson, Farouk Nathoo
Time series analysis of fMRI data is an important area of medical statistics for neuroimaging data. The neuroimaging community has embraced mean-field variational Bayes (VB) approx…
Atmospheric boundary layer over urban roughness: validation of large-eddy simulation
Ming Teng, Josep M. Duró Diaz, Ernest Mestres +3
The study presents wall-modeled large-eddy simulations (LES) characterizing the flow features of a neutral atmospheric boundary layer over two urban-like roughness geometries: an a…
Impact of Wind Direction on Flow Over a Realistic Urban Area: A Large-Eddy Simulation Study
Ivette RodrÃguez, Josep Maria Duró, Ernest Mestres +2
We conducted high-resolution large-eddy simulations over a real urban district in Barcelona to examine the impact of wind direction on near-ground flow. The computational mesh reso…
Bayesian Computation for Log-Gaussian Cox Processes--A Comparative Analysis of Methods
Ming Teng, Farouk S. Nathoo, Timothy D. Johnson
The Log-Gaussian Cox Process is a commonly used model for the analysis of spatial point patterns. Fitting this model is difficult because of its doubly-stochastic property, i.e., i…