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Comparative Visual Analysis of Lagrangian Transport in CFD Ensembles
"... Fig. 1. An ensemble of a 2D convection flow field is analyzed using the proposed joint variance visualization techniques. From left to right: Individual variances of four of the data set runs show high variances around the heating cylinder. Brushing in the classification space allows for the identif ..."
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Cited by 1 (0 self)
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in their output. For ensembles of timevarying vector fields, there are numerous challenges for providing an expressive comparative visualization, among which is the requirement to relate the effect of individual flow divergence to joint transport characteristics of the ensemble. Yet, techniques developed
Online Submission ID: 271 Comparative Visual Analysis of Lagrangian Transport in CFD Ensembles
"... Fig. 1. An ensemble of a 2D convection flow field is analyzed using the proposed joint variance visualization techniques. From left to right: Individual variances of four of the data set runs show high variances around the heating cylinder. Brushing in the classification space allows for the identif ..."
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in their output. For ensembles of timevarying vector fields, there are numerous challenges for providing an expressive comparative visualization, among which is the requirement to relate the effect of individual flow divergence to joint transport characteristics of the ensemble. Yet, techniques developed
Glyphs for Visualizing Uncertainty in Environmental Vector Fields
 IEEE Transactions on Visualization and Computer Graphics
, 1995
"... Environmental data have inherent uncertainty which is often ignored in visualization. For example, meteorological stations measure wind with good accuracy, but winds are often averaged over minutes or hours. As another example, doppler radars (wind profilers and ocean current radars) take thousands ..."
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Cited by 15 (3 self)
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of samples and average the possibly spurious returns. Others, including time series data have a wealth of uncertainty information, that the traditional vector visualization methods such as using wind barbs and arrow glyphs simply ignore. We have developed new vector glyphs to visualize uncertain winds
Nonparametric Models for Uncertainty Visualization
"... An uncertain (scalar, vector, tensor) field is usually perceived as a discrete random field with a priori unknown probability distributions. To compute derived probabilities, e.g. for the occurrence of certain features, an appropriate probabilistic model has to be selected. The majority of previous ..."
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An uncertain (scalar, vector, tensor) field is usually perceived as a discrete random field with a priori unknown probability distributions. To compute derived probabilities, e.g. for the occurrence of certain features, an appropriate probabilistic model has to be selected. The majority
Uncertain 2D vector field topology
 COMPUT. GRAPH. FORUM
"... We introduce an approach to visualize stationary 2D vector fields with global uncertainty obtained by considering the transport of local uncertainty in the flow. For this, we extend the concept of vector field topology to uncertain vector fields by considering the vector field as a density distribut ..."
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Cited by 22 (8 self)
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We introduce an approach to visualize stationary 2D vector fields with global uncertainty obtained by considering the transport of local uncertainty in the flow. For this, we extend the concept of vector field topology to uncertain vector fields by considering the vector field as a density
2004), Firstorder variance of travel time in nonstationary formations
 Water Resour. Res
"... [1] Evaluating uncertainty in solute transport under nonstationary flow conditions is a computationally demanding task. This is particularly true for cases with a twopoint covariance function of log conductivity depending on the actual positions of the points rather than their distance vector. Thes ..."
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Cited by 4 (3 self)
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[1] Evaluating uncertainty in solute transport under nonstationary flow conditions is a computationally demanding task. This is particularly true for cases with a twopoint covariance function of log conductivity depending on the actual positions of the points rather than their distance vector
Ensemble clustering in visual working memory biases location memories and reduces the Weber noise of relative positions
"... People seem to compute the ensemble statistics of objects and use this information to support the recall of individual objects in visual working memory. However, there are many different ways that hierarchical structure might be encoded. We examined the format of structured memories by asking subje ..."
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ways in which hierarchical encoding improves the fidelity of visual working memory. First, objects are biased toward their ensemble statistics to compensate for uncertainty about individual object properties. Second, objects are encoded relative to their parents in the hierarchy, and relative positions
Tellus (2011), 63A, 585–604 C © 2011 The Authors
, 2010
"... Highresolution ensemble prediction of a polar low development ..."
Exploring Traffic Dynamics in Urban Environments Using VectorValued Functions
"... The traffic infrastructure greatly impacts the quality of life in urban environments. To optimize this infrastructure, engineers and decision makers need to explore traffic data. In doing so, they face two important challenges: the sparseness of speed sensors that cover only a limited number of road ..."
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taxi trips contain neither the location of taxis at frequent intervals nor their routes. We propose an efficient traffic model to derive speed and direction information from these data, and show that it provides reliable estimates. Using these estimates, we define a timevarying vectorvalued function
V.: Gaussian mixture model based volume visualization
 In Large Data Analysis and Visualization (LDAV), 2012 IEEE Symposium on (2012), IEEE
"... Figure 1: An ensemble of air temperatures created by combining the daily temperatures for the month of January (31 days) over a 29 year period on a three dimensional grid of dimension 256×128×31. (a) The mean data and transfer function. (b)(e) Screen space accumulated integration of Gaussian mixtur ..."
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Cited by 2 (0 self)
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mixture model representations of the data, using one, two, four, and six components, respectively. Representing uncertainty when creating visualizations is becoming more indispensable to understand and analyze scientific data. Uncertainty may come from different sources, such as, ensembles of experiments
Results 1  10
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126