BACKGROUND Polymer gel dosimeters combined with magnetic resonance imaging (MRI) can be used for dose verification of advanced radiation therapy techniques. However, the uncertainty of dose map measured by gel dosimeter should be known. The purpose of this study is to investigate the uncertainty related to calibration curve and MRI protocol for MAGIC (Methacrylic and Ascorbic acid in Gelatin In...

BACKGROUND Uncertainty shapes our perception of the world and the decisions we make. Two aspects of uncertainty are commonly distinguished: uncertainty in previously acquired knowledge (prior) and uncertainty in current sensory information (likelihood). Previous studies have established that humans can take both types of uncertainty into account, often in a way predicted by Bayesian statistics....

The utility of land-cover change data is often derived from the intersection with other information, such as riparian buffers zones or other areas of conservation concern. In order to avoid error propagation, we wanted to optimize our change maps to have very low error rates. Our accuracy optimization methods doubled the number of total change locations mapped, and also increased the area of de...

This paper examines the impact of the concentration of the property insurance industry on economic growth in China. We first compute the Herfindahl-Hirschman Index (HHI) for the Chinese property insurance industry and establish a two-step system of generalized methods of moments (Two-Step SYS-GMM) estimation to compute the economic effect using a unique data set from the years 1980 to 2014. The...

Motion planning under uncertainty is an important problem in robotics. Although probabilistic sampling is highly successful for motion planning of robots with many degrees of freedom, sampling-based algorithms typically ignore uncertainty during planning. We introduce the notion of a bounded uncertainty roadmap (BURM) and use it to extend samplingbased algorithms for planning under uncertainty ...

Global Sensitivity Analysis (GSA) methods are useful tools to rank input parameters uncertainties regarding their impact on result variability. In practice, such type of approach is still at an exploratory level for studies relying on 2D Shallow Water Equations (SWE) codes as GSA requires specific tools and deals with important computational capacity. The aim of this paper is to provide both a ...

We present an approach to the problem of representing images that contain multiple objects or surfaces. Rather than use an edge-based approach to represent the segmentation of a scene, we propose a multi-layer estimation framework which uses support maps to represent the segmentation of the image into homogeneous chunks. This support-based approach can represent objects that are split into disj...

Causal or conditional probability networks (CPNs) are shown to provide a natural framework for combining a time sequence of classified satellite images with other maps for environmental monitoring. The key features of CPNs are described by way of application to an example involving the monitoring of salinisation of farmland over time using satellite images and an ancillary data set derived from...

Spatial decision support systems (SDSS) are designed to make complex resource allocation problems more transparent and to support the design and evaluation of allocation plans. Recent developments in this field focus on the design of allocation plans using optimization techniques. In this paper we analyze how uncertainty in spatial (input) data propagates through, and affects the results of, an...

This thesis consists of two parts which share only a slight overlap. The first part is concerned with the study of ideals in the ring C ∞ (M, R) of smooth functions on a compact smooth manifold M or more generally submodules of a finitely generated C ∞ (M, R)-module V. We define a topology on the space M d (V) of all submodules of V of a fixed finite codimension d. Its main property is that it ...