Search results for "uncertainty."
showing 10 items of 972 documents
Using of a uncertainty model of an polyarticulated coordinates measuring arm to validate the measurement in a manufacturing processsus
2014
International audience; Coordinates Measuring Arms (CMA) are increasingly used to control industrial parts and are often an alternative to CMM controls that require conditions of laboratory measurement and involve significant costs. However, the control of uncertainties is often not guaranteed because the measurement process is complex and there is no standard for setting a framework qualification process of the measurement process.The proposed study, in this paper, is a first approach to model the measurement uncertainties of a CMA with contact sensor. The problem is complex because there are many sources of uncertainty, largely due to variability in the handling carried out by the operato…
Taking digitized points quality into account in geometrical specification measurement by laser sensor
2004
International audience; Today, the new measurement techniques without contact like the laser sensors are used more and more in industrial applications. They allow to obtain many points in a short time. However these techniques have a less good accuracy than the classical process with contact probe for metrology application. The work presented in this paper, is part of a research project on the in-process product inspection. In the case of in-process product inspection, the throughput time must be the shortest with a good dimensional accuracy. So, it is necessary to increase the measurement accuracy of the points cloud for using the laser scanners. For this first approach, we suggest to buil…
3D surfaces automated acquisition using non contact sensor with repect of metrological conditions
2013
International audience
Uncertainty-reducing cooperation scripts in online learning environments
2004
Online learning courses can create new interaction situations for participants who have not previously worked with each other. Initially, there is some degree of uncertainty between participants in these interaction situations. According to the uncertainty reduction theory, low uncertainty increases theamount of discourse and decreases information seeking. Thus, uncertainty may influence online discourseand learning. However, the relation of uncertainty reduction to learning outcomes has not yet been investigated systematically. Cooperation scripts may reduce uncertainty, and therefore enhance learning.A cooperation script, which aims to reduce uncertainty at a cognitive level, was chosen f…
Bridging Sensing and Decision Making in Ambient Intelligence Environments
2009
Context-aware and Ambient Intelligence environments represent one of the emerging issues in the last decade. In such intelligent environments, information is gathered to provide, on one hand, autonomic and easy to manage applications, and, on the other, secured access controlled environments. Several approaches have been defined in the literature to describe context-aware application with techniques to capture and represent information related to a specified domain. However and to the best of our knowledge, none has questioned the reliability of the techniques used to extract meaningful knowledge needed for decision making especially if the information captured is of multimedia types (image…
Leveraging Uncertainty Estimates to Improve Segmentation Performance in Cardiac MR
2021
International audience; In medical image segmentation, several studies have used Bayesian neural networks to segment and quantify the uncertainty of the images. These studies show that there might be an increased epistemic uncertainty in areas where there are semantically and visually challenging pixels. The uncertain areas of the image can be of a great interest as they can possibly indicate the regions of incorrect segmentation. To leverage the uncertainty information, we propose a segmentation model that incorporates the uncertainty into its learning process. Firstly, we generate the uncertainty estimate (sample variance) using Monte-Carlo dropout during training. Then we incorporate it …
Using Polynomial Loss and Uncertainty Information for Robust Left Atrial and Scar Quantification and Segmentation
2022
Automatic and accurate segmentation of the left atrial (LA) cavity and scar can be helpful for the diagnosis and prognosis of patients with atrial fibrillation. However, automating the segmentation can be difficult due to the poor image quality, variable LA shapes, and small discrete regions of LA scars. In this paper, we proposed a fully-automatic method to segment LA cavity and scar from Late Gadolinium Enhancement (LGE) MRIs. For the loss functions, we propose two different losses for each task. To enhance the segmentation of LA cavity from the multicenter dataset, we present a hybrid loss that leverages Dice loss with a polynomial version of cross-entropy loss (PolyCE). We also utilize …
How to Enrich Description Logics with Fuzziness
2017
International audience; The paper describes the relation between fuzzy and non-fuzzy description logics. It gives an overview about current research in these areas and describes the difference between tasks for description logics and fuzzy logics. The paper also deals with the transformation properties of description logics to fuzzy logics and backwards. While the process of transformation from a description logic to a fuzzy logic is a trivial inclusion, the other way of reducing information from fuzzy logic to description logic is a difficult task, that will be topic of future work.
Automated uncertainty quantification analysis using a system model and data
2015
International audience; Understanding the sources of, and quantifying the magnitude of, uncertainty can improve decision-making and, thereby, make manufacturing systems more efficient. Achieving this goal requires knowledge in two separate domains: data science and manufacturing. In this paper, we focus on quantifying uncertainty, usually called uncertainty quantification (UQ). More specifically, we propose a methodology to perform UQ automatically using Bayesian networks (BN) constructed from three types of sources: a descriptive system model, physics-based mathematical models, and data. The system model is a high-level model describing the system and its parameters; we develop this model …
Calcul des contributions des incertitudes dans un modèle complexe de qualité de l'eau
2010
The quantification of uncertainty in integrated urban drainage water quality models is of paramount interest. Indeed, the assessment of the reliability of the model results for complex water quality models is useful for understanding the significance of the results. However, the state of knowledge regarding uncertainties in urban drainage models is poor. In the case of integrated urban drainage water quality models, due to the fact that integrated approaches are basically a cascade of sub-models (simulating sewer system, wastewater treatment plant and receiving water body), the uncertainty produced in one sub-model propagates to the following ones depending on the model structure, the estim…