Bayesian data fusion applied to water table spatial mapping

Bayesian Prediction in Spatial Data Analysis

Buried Utility Pipeline Mapping Based on Multiple Spatial Data Sources: A Bayesian Data Fusion Approach

Statutory records of underground utility apparatus (such as pipes and cables) are notoriously inaccurate, so street surveys are usually undertaken before road excavation takes place to minimize the extent and duration of excavation and for health and safety reasons. This involves the use of sensors such as Ground Penetrating Radar (GPR). The GPR scans are then manually interpreted and combined ...

Bayesian Analysis of Survival Data with Spatial Correlation

Often in practice the data on the mortality of a living unit correlation is due to the location of the observations in the study‎. ‎One of the most important issues in the analysis of survival data with spatial dependence‎, ‎is estimation of the parameters and prediction of the unknown values in known sites based on observations vector‎. ‎In this paper to analyze this type of survival‎, ‎Cox...

Data mining applied to linkage disequilibrium mapping.

We introduce a new method for linkage disequilibrium mapping: haplotype pattern mining (HPM). The method, inspired by data mining methods, is based on discovery of recurrent patterns. We define a class of useful haplotype patterns in genetic case-control data and use the algorithm for finding disease-associated haplotypes. The haplotypes are ordered by their strength of association with the phe...

A Bayesian Multisensor Fusion Approach Integrating Correlated Data applied to a Real-time Pedestrian Detection System

The pedestrian detection is a challenging task in automotive research, which often suffers from the lack of reliability due to the occurrences of spurious detections. This paper presents a Bayesian approach, which fuse information from multiple sensors to improve the performances of a pedestrian detection system. The main contribution of this paper is the way to incorporate the information pote...