This paper presents a simulation-based framework for sequential inference from partially and discretely observed point process models with static parameters. Taking on a Bayesian perspective for the static parameters, we build upon sequential Monte Carlo methods, investigating the problems of...

This research evaluated the impact of three rainfall datasets on hydrologic process simulations in two coastal catchments located in Alabama. In this study, rain gauge time series recorded by the U.S. National Oceanic and Atmospheric Administration (NOAA) and Geological Survey (USGS) along with...

Computer intelligence won't ever match human intelligence, but it will soon be absolutely essential to business success.

The gap between higher learning practices and business expectations in terms of preparing engineering, technology, and business students is significant. This paper offers an innovative approach toward narrowing that gap. The approach offered stresses an open system orientation and partnerships...