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Uncertainty and Sensitivity Assessments of GPS and GIS Integrated Applications for Transportation

Sungchul Hong, Alan Vonderohe
2014 Sensors  
However, for the distance-based computational model, output information has a different magnitude of uncertainties, depending on position uncertainties in input data.  ...  In the methods, an error model and an error propagation method form a basis for formulating characterization and propagation of uncertainties.  ...  Author Contributions This paper is based on a research for my Ph.D. dissertation, and this research was conducted under guidance of Prof. Alan P. Vonderohe.  ... 
doi:10.3390/s140202683 pmid:24518894 pmcid:PMC3958225 fatcat:f7m2qy552bbd3fv7xs7notgcnm

When Ignorance Is Bliss The Role of Motivation to Reduce Uncertainty in Uncertainty Reduction Theory

KATHY KELLERMANN, RODNEY REYNOLDS
1990 Human Communication Research  
Rather, folerance for uncertainty (Model 3) isone of threedeterminants of information seeking, while level of uncertainty (Model I ) is one of three determinants of attraction.  ...  of tolerance for uncertainty, the rejection of Axiom 3 in uncertainty reduction theory (which specifies a positive relationship between uncertainty and information seeking), and the rejection of Theorem  ...  Rather, tolerance for uncertainty (Model 3) was one of three determinants of information seeking, while uncertainty (Model 1) was one of three determinants of attraction.  ... 
doi:10.1111/j.1468-2958.1990.tb00226.x fatcat:zybp6pj2xva7vnhd7c5baq77ta

Bayesian models: the structure of the world, uncertainty, behavior, and the brain

Iris Vilares, Konrad Kording
2011 Annals of the New York Academy of Sciences  
Experiments on humans and other animals have shown that uncertainty due to unreliable or incomplete information affects behavior.  ...  This formalization results in a wide range of Bayesian models that derive from assumptions about the world, and it often seems unclear how these models relate to one another.  ...  We also want to thank Hugo Fernandes and Mark Albert for helpful comments on the manuscript.  ... 
doi:10.1111/j.1749-6632.2011.05965.x pmid:21486294 pmcid:PMC3079291 fatcat:5eatrdgmsvdsbpxq35lcze6edu

Testing Links Among Uncertainty, Affect, and Attitude Toward a Health Behavior

Timothy K. F. Fung, Robert J. Griffin, Sharon Dunwoody
2018 Science communication  
It uses data from a longitudinal study (n = 334) of people's reactions to the risks of eating contaminated fish from the Great Lakes, which employed the Risk Information Seeking and Processing model, and  ...  Findings support the expanded model and indicate that worry and anger strongly influenced uncertainty judgments, but anger and worry influenced attitudes toward fish avoidance and information insufficiency  ...  However, while perceived threat to future generations had a significant positive impact on worry, its impact on anger was negligible.  ... 
doi:10.1177/1075547017748947 fatcat:4bqxflfozbf2zcscqem3476r34

The improvement of uncertainty measurements accuracy in sensor networks based on fuzzy dempster-shafer theory

Ehsan Azimirad, Seyyed Reza Movahhed Ghodsinya
2020 IJAIN (International Journal of Advances in Intelligent Informatics)  
In this paper, a model-based uncertainty is presented in the air defense system based on the Fuzzy Dempster-Shafer Theory to measure uncertainty and its accuracy.  ...  In literature, there are some theories that state and model uncertainty in the information. One of the new methods is the Fuzzy Dempster-Shafer Theory.  ...  No additional information is available for this paper.  ... 
doi:10.26555/ijain.v6i2.461 fatcat:jujyj6ya7fh7jlhb2d4s5rapze

The Generalization of Prior Uncertainty during Reaching

H. L. Fernandes, I. H. Stevenson, I. Vilares, K. P. Kording
2014 Journal of Neuroscience  
Bayesian statistics defines how new information, given by a likelihood, should be combined with previously acquired information, given by a prior distribution.  ...  In particular, we look into how the first two moments of the prior-the mean and variance (uncertainty)-generalize.  ...  A-D, Model comparison for Models T and VF for Uncertainty (A, B) and for Mean (C, D).  ... 
doi:10.1523/jneurosci.3882-13.2014 pmid:25143626 pmcid:PMC4138350 fatcat:vi77bxlqgjdgxjxoz5cuuwejzu

A probabilistic framework for representing and simulating uncertain environmental variables

G. B. M. Heuvelink, J. D. Brown, E. E. van Loon
2007 International Journal of Geographical Information Science  
Acknowledgements The present work was carried out within the Project 'Harmonised Techniques and Representative River Basin Data for Assessment and Use of Uncertainty Information in Integrated Water Management  ...  Probability models for positional and attribute uncertainty Each of the categories of uncertain objects and attributes (above) is associated with a general pdf.  ...  Estimation of the general pdfs In order to apply one of the general pdfs for positional or attribute uncertainty to a particular case, each possible outcome of the pdf and its associated probability must  ... 
doi:10.1080/13658810601063951 fatcat:hmbsdy56ujerzbviq3awwdgfiq

Onto computing the uncertainty for the odometry pose estimate of a mobile robot

Josep M. Mirats Tur
2007 2007 IEEE Conference on Emerging Technologies & Factory Automation (EFTA 2007)  
In a previous work, a general method to obtain the uncertainty in the odometry pose estimate was proposed.  ...  Here, with the aim of assessing the generality of the method, the general formulation is particularized for a given differential driven robot.  ...  This is not fully consistent with the experiment run, because only one source of position information has been used to compute the position of the robot, so there is no extra information so as to decrease  ... 
doi:10.1109/efta.2007.4416936 dblp:conf/etfa/Tur07 fatcat:vodtlsjgljdx3jzkbuexabjyaa

Uncertainty and Value of Information in Risk Prediction Modeling [article]

Mohsen Sadatsafavi, Tae Yoon Lee, Paul Gustafson
2021 arXiv   pre-print
We apply Value of Information methodology to evaluate the decision-theoretic implications of prediction uncertainty.  ...  Results: With a sample size of 1,000 and at the pre-specified threshold of 2% on predicted risks, the gain in net benefit by using the proposed and the correct models were 0.0006 and 0.0011, respectively  ...  Nonetheless, Value of Information in decision analysis is justified based on the working assumption that a model that is good enough for calculating net benefit is also good enough for quantifying uncertainty  ... 
arXiv:2106.10721v3 fatcat:cpqgjbemvneizbd3ynzx7sx63m

Uncertainty relation for the position of an electron in a uniform magnetic field from quantum estimation theory [article]

Shin Funada, Jun Suzuki
2020 arXiv   pre-print
We investigate the uncertainty relation for estimating the position of one electron in a uniform magnetic field in the framework of the quantum estimation theory.  ...  Two kinds of momenta, canonical one and mechanical one, are used to generate a shift in the position of the electron.  ...  Hiroshi Nagaoka for the invaluable discussion and suggestion. We would also like to thank anonymous referees for constructive discussions to improve the manuscript.  ... 
arXiv:1908.04868v2 fatcat:xupfbrojtvboxak4unjtidjkyi

Validating 3-D Structural Models with Geological Knowledge for Improved Uncertainty Evaluations

J. Florian Wellmann, Mark Lindsay, Jonathan Poh, Mark Jessell
2014 Energy Procedia  
Several stochastic approaches have recently been developed to evaluate uncertainties in 3-D geological models based on imprecise geological data.  ...  We present here a method to enable automatic checks of models based on reliability filters encapsulating aspects of geological knowledge.  ...  In the example case of a model representing a graben structure, constraints based on additional information (min/max position and thickness of a layer) and on the geological evolution of an area (type  ... 
doi:10.1016/j.egypro.2014.10.391 fatcat:mwm6npnn6nairdd4c7k2gjzeq4

Uncertainty and Political Perceptions

R. Michael Alvarez, Charles H. Franklin
1994 Journal of Politics  
Next, we estimated similar models examining the uncertainty responses for the Senator's issue positions. One problem for estimation of the response models is the presence of selection bias.  ...  For example, to place a moderate on an issue scale, the respondent needs a good deal of information -but not so for an extremist.  ... 
doi:10.2307/2132187 fatcat:cvlebr6nvvepzh4irq2tulllee

Improving Pose Estimation Using Image, Sensor and Model Uncertainty

V. Caglioti, F. Mainardi, M. Pilu, D. G. Sorrenti
1994 Procedings of the British Machine Vision Conference 1994  
This work proposes a methodology for the analysis of the uncertainty in the localization of objects when considering uncertain image data, camera and object geometry parameters.  ...  At the end of the process, a better estimate of the object pose with its uncertainty is given along with a new estimate of the used uncertain object features and the camera parameters.  ...  The authors want to thank David Wren and Andrew Fitzgibbon for proofreading the final document.  ... 
doi:10.5244/c.8.78 dblp:conf/bmvc/CagliotiMPS94 fatcat:4jhfv5kzuzahppfjpl4d246hdu

Visualisation of Spatial Data Uncertainty. A Case Study of a Database of Topographic Objects

Ślusarski, Jurkiewicz
2019 ISPRS International Journal of Geo-Information  
Fill grain density and contour crispness were employed to represent the positional uncertainty for surface objects.  ...  The positional uncertainty for point objects was presented using visual variables, object fill with hue colour and lightness, and glyphs placed at map symbol positions.  ...  Data quality information is often generated and visualised using a scale for which the detail level of data uncertainty features presentation is optimised.  ... 
doi:10.3390/ijgi9010016 fatcat:bwtiypmw6jehjn2o5f4phdux2q

Projecting species' vulnerability to climate change: Which uncertainty sources matter most and extrapolate best?

Valerie Steen, Helen R. Sofaer, Susan K. Skagen, Andrea J. Ray, Barry R. Noon
2017 Ecology and Evolution  
Given uncertainty in projected vulnerability and resulting uncertainty in rankings used for conservation prioritization, a number of considerations appear critical for using bioclimatic SDMs to inform  ...  K E Y W O R D S bioclimatic species distribution models, climate change vulnerability, climate covariates, collinearity, general circulation models, Prairie Pothole Region, projection uncertainty, thresholds  ...  Compared to the hydrological hypothesis, the temporal hypothesis generally had a positive impact on extrapolation ability, while the bioclimatic hypothesis generally had a negative impact.  ... 
doi:10.1002/ece3.3403 pmid:29152181 pmcid:PMC5677485 fatcat:exdok4ljdfdlflswb6ukji5tc4
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