Well log data are a common source of information for characterizing subsurface environments. A statistical methodology is developed and applied for the interpretation of such data in terms of a multi-state depositional sequence. The well log data is classified into a discrete set of states (e.g., sand, silt, clay) and stratigraphic transitions between these… (More)
Connected zones of high hydraulic conductivity in subsurface environments can constitute preferential pathways for contaminant transport and fluid flow. The identification of such pathways is important for well head protection, groundwater monitoring and capture system design for groundwater remediation. Since it is not practical to exhaustively sample the… (More)
Subsurface characterization is important for investigations of groundwater contamination as well as petroleum extraction potential. Bore holes or drill logs are a common source of localized stratigraphic information. Sampling and interpolation uncertainties complicate the characterization of the subsurface from these data. Geostatistical methods (Kriging… (More)
Automatic object detection is a rapidly evolving area in surveillance and autonomous vehicles. Deformable part model (DPM) is a well-known object detector for its high precision and speed bottleneck. This paper proposes a very fast object detection pipeline based on complementary techniques to accelerate DPM. A recent fast feature pyramid technique is… (More)
2 ACKNOWLEDGEMENTS The Adaptive Protocols for Lake Okeechobee Operations were developed to provide guidance in operations for protection of Lake Okeechobee and downstream ecosystems while providing a reliable water supply for agricultural and urban areas that depend on the Lake.
A nonparametric statistical tool based on kernel function estimation is developed for spatial rainfall characterization. In this method, observations closer to the point of estimate are weighted higher using kernel function with a prescribed bandwidth. The kernel bandwidth is local and it extends only to the K th Nearest Neighbor, KNN, observation. An… (More)