In urban planning, sophisticated simulation models are key tools to estimate future population growth for measuring the impact of planning decisions on urban developments and the environment. Simulated population projections usually result in bulky, large-scale, multivariate geospatial data sets. Millions of records have to be processed, stored, and visualized to help planners explore and analy...

Several methods for generating random variables with univariate and multivariate Wallenius' and Fisher's noncentral hypergeometric distributions are developed. Methods for the univariate distributions include: simulation of urn experiments, inversion by binary search, inversion by chop-down search from the mode, ratio-of-uniforms rejection method, and rejection by sampling in the t domain. Meth...

Several methods for generating random variables with univariate and multivariate Wallenius' and Fisher's noncentral hypergeometric distributions are developed. Methods for the univariate distributions include: simulation of urn experiments, inversion by binary search, inversion by chop-down search from the mode, ratio-of-uniforms rejection method, and rejection by sampling in the t domain. Meth...

Visualization of multivariate dataset has a great importance on understanding numerical simulation results. Meanwhile, there are few reports on effective application to geophysical fluid simulation dataset. In this study, we apply multidimensional transfer functions which can represent two or three physical variables simultaneously to geophysical fluid simulation such as global ocean model and ...

Sophisticated simulation models are now extensively used in urban planning for estimating future population and job distributions to measure the impact of planning decisions on future urban environments. Simulated population projections usually result in large, macro-scale, and multivariate geospatial data sets. Millions of records have to be processed, stored, and visualized to help planners e...

Simulations of complex scientific phenomena involve the execution of massively parallel computer programs. These simulation programs generate large-scale data sets over the spatio-temporal space. Modeling such massive data sets is an essential step in helping scientists discover new information from their computer simulations. In this paper, we present a simple but effective multivariate cluste...