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Multivariate visualization of 3D turbulent flow data

Sheng-Wen Wang, Victoria Interrante, Ellen Longmire, Jinah Park, Ming C. Hao, Pak C. Wong, Chaomei Chen
2010 Visualization and Data Analysis 2010  
We demonstrate our methods on a range of data including 3D turbulent boundary flow data and time varying ring data.  ...  Turbulent flows play a critical role in many fields, yet our understanding of the fundamental physics of turbulence remains in its infancy.  ...  ACKNOWLEDGMENTS We would like to thank Neelakantan Saikrishnan and Daniel R. Troolin for providing us with the flow datasets and assisting us in working with them.  ... 
doi:10.1117/12.839093 dblp:conf/vda/WangIL10 fatcat:uyzva6btbbfrfai5ylkrbmui5e

Visual Analysis of Large Multivariate Scattered Data using Clustering and Probabilistic Summaries [article]

Tobias Rapp, Christoph Peters, Carsten Dachsbacher
2020 arXiv   pre-print
Rapidly growing data sizes of scientific simulations pose significant challenges for interactive visualization and analysis techniques.  ...  We observe that it suffices to consider low-dimensional marginal distributions for two or three data dimensions at a time to employ common visual analysis techniques.  ...  The Hurricane Isabel data is courtesy of NCAR, and the U.S. National Science Foundation (NSF).  ... 
arXiv:2008.09544v1 fatcat:7hascskpknhengpclfgxmixngu

Analysis Guided Visual Exploration of Multivariate Data

Di Yang, Elke A. Rundensteiner, Matthew O. Ward
2007 2007 IEEE Symposium on Visual Analytics Science and Technology  
To evaluate the effectiveness of NMS, we integrated NMS into Xmd-vTool, a freeware multivariate visualization system.  ...  To solve the problem of inaccurate discoveries, localized data mining techniques are applied to refine the nuggets to best represent the captured patterns in datasets.  ...  We also thank members of DSRG at WPI for listening to talks and providing input on this work.  ... 
doi:10.1109/vast.2007.4389000 dblp:conf/ieeevast/YangRW07 fatcat:djwwjny4vvgphkvknvw3lbheta

Visual Analysis of Multivariate Movement Data using Interactive Difference Views [article]

Ove Daae Lampe, Johannes Kehrer, Helwig Hauser
2010 International Symposium on Vision, Modeling, and Visualization  
Movement data consisting of a large number of spatio-temporal agent trajectories is challenging to visualize, especially when all trajectories are attributed with multiple variates.  ...  in terms of the units of the visualized data.  ...  The work presented here is a part of the project "e-Centre Laboratory for Automated Drilling Processes" (eLAD  ... 
doi:10.2312/pe/vmv/vmv10/315-322 dblp:conf/vmv/LampeKH10 fatcat:36bexlzbrfdd3owb65pbtxk3sy

Inferential and visual analysis of ethogram data using multivariate techniques

Richard Stafford, Anne E. Goodenough, Kathy Slater, William Carpenter, Laura Collins, Heather Cruickshank, Sarah Downing, Sally Hall, Katie McDonald, Heather McDonnell, Bryony Overs, Lizzie Spiers (+3 others)
2012 Animal Behaviour  
2011) Inferential and visual analysis of ethogram data using multivariate techniques. Animal Behaviour, 83 (2). pp. 563-569. ISSN 00033472 Official URL: http://dx.  ...  Acknowledgements 328 The autho s ould like to tha k Hei z Koh s, di e to of Spa e fo 329 Elepha ts project and Cheltenham Animal Shelter for their assistance in with this study.  ...  , would not make a significant 319 difference to the outcome of the analysis. 320 The technique presented here provides an excellent framework for visualising activity 321 budget collected data and provides  ... 
doi:10.1016/j.anbehav.2011.11.020 fatcat:5cn545erbra4zp74hha4izxjpy

DataMeadow: A Visual Canvas for Analysis of Large-Scale Multivariate Data

Niklas Elmqvist, John Stasko, Philippas Tsigas
2007 2007 IEEE Symposium on Visual Analytics Science and Technology  
Towards this end, the DataMeadow has a direct manipulation interface for selection, filtering, and creation of sets, subsets, and data dependencies using both simple and complex mouse gestures.  ...  A DataRose is essentially a starplot of selected columns in a dataset displayed as multivariate visualizations with dynamic query sliders integrated into each axis.  ...  DataMeadow The DataMeadow is an infinite 2D canvas and a collection of visual analysis elements used for multivariate visual exploration.  ... 
doi:10.1109/vast.2007.4389013 dblp:conf/ieeevast/ElmqvistST07 fatcat:esrsmhnnpnburgesebzwiv5l2e

Association Rules-Based Multivariate Analysis and Visualization of Spatiotemporal Climate Data

Feng Wang, Wenwen Li, Sizhe Wang, Chris Johnson
2018 ISPRS International Journal of Geo-Information  
Three techniques are introduced: (1) web-based spatiotemporal climate data visualization; (2) multiview and multivariate scientific data analysis; and (3) data mining-enabled visual analytics.  ...  This work also provides techniques for identifying multivariate correlation and for better understanding the driving factors of climate phenomena.  ...  Acknowledgments: The authors would like to thank all the reviewers for their constructive comments to improve the manuscript. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/ijgi7070266 fatcat:nf72gpftnvafbao6h7uxnq2o3e

Error-bounded reduction of triangle meshes with multivariate data

Chandrajit L. Bajaj, Daniel R. Schikore, Georges G. Grinstein, Robert F. Erbacher
1996 Visual Data Exploration and Analysis III  
the introduced error in both the geometry and the multivariate data.  ...  We extend these methods to arbitrary surfaces in 3D and to any number of variables defined over the mesh by developing a algorithm for mapping from a surface mesh to a reduced representation and measuring  ...  Acknowledgements We are grateful to Lawrence Livermore National Lab for access to the pion collision and projectile impact data sets.  ... 
doi:10.1117/12.234689 fatcat:kpq4spkzmrgzxor6iyd3ma3lxy

Temporal MDS Plots for Analysis of Multivariate Data

Dominik Jackle, Fabian Fischer, Tobias Schreck, Daniel A. Keim
2016 IEEE Transactions on Visualization and Computer Graphics  
Dimensionality reduction methods such as PCA and MDS allow analysis and visualization of multivariate data, but per se do not provide means to explore multivariate patterns over time.  ...  We propose Temporal Multidimensional Scaling (TMDS), a novel visualization technique that computes temporal one-dimensional MDS plots for multivariate data which evolve over time.  ...  ACKNOWLEDGMENTS We are thankful to Ming Hao and Wei-Nchih Lee of Hewlett-Packard Labs for fruitful discussions on multivariate data analysis and an earlier instance of the solution.  ... 
doi:10.1109/tvcg.2015.2467553 pmid:26529694 fatcat:sqkv2f4u5fh2nkakexeb5wat5y

Evaluation of multivariate visualizations: a case study of refinements and user experience

Mark A. Livingston, Jonathan W. Decker, Pak Chung Wong, David L. Kao, Ming C. Hao, Chaomei Chen, Robert Kosara, Mark A. Livingston, Jinah Park, Ian Roberts
2012 Visualization and Data Analysis 2012  
Multivariate visualization (MVV) aims to provide insight into complex data sets with many variables.  ...  , searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information.  ...  the data points used for analysis.  ... 
doi:10.1117/12.912192 dblp:conf/vda/LivingstonD12 fatcat:m6bjjmrzu5bqdc5qqrujzufay4

An Application of Multivariate Statistical Analysis for Query-Driven Visualization

L J Gosink, C Garth, J C Anderson, E W Bethel, K I Joy
2011 IEEE Transactions on Visualization and Computer Graphics  
Query-Driven Visualization (QDV) strategies are among the small subset of techniques that can address both large and highly complex datasets.  ...  This paper extends the utility of QDV strategies with a statistics-based framework that integrates non-parametric distribution estimation techniques with a new segmentation strategy to visually identify  ...  We also thank our reviewers for helping to improve this paper. Last a warm acknowledgement goes to George Roussas who inspired this work in earlier conversations.  ... 
doi:10.1109/tvcg.2010.80 pmid:20498506 fatcat:m3lq545zxvaoregntg5q5g74xy

A comparison of fMRI adaptation and multivariate pattern classification analysis in visual cortex

Panagiotis Sapountzis, Denis Schluppeck, Richard Bowtell, Jonathan W. Peirce
2010 NeuroImage  
Here, we compared fMRI results from orientation-specific visual adaptation and orientation-classification by MVPA, using optimized experimental designs for each, and found that the multivariate pattern  ...  The second technique, multivariate pattern analysis (MVPA), makes use of multivariate statistics to recover small biases in individual voxels in their responses to different stimuli.  ...  Andrew Smith and Prof. Zoe Kourtzi for their constructive comments.  ... 
doi:10.1016/j.neuroimage.2009.09.066 pmid:19815081 pmcid:PMC2793370 fatcat:u2trv47rovdjpnxqicu7zsmjlq

Raman spectroscopy of uranium compounds and the use of multivariate analysis for visualization and classification

Doris Mer Lin Ho, Andrew E. Jones, John Y. Goulermas, Philip Turner, Zsolt Varga, Lorenzo Fongaro, Thomas Fanghänel, Klaus Mayer
2015 Forensic Science International  
The spectra obtained from 9 different classes of chemical compounds were subjected to multivariate data analysis such as principal component analysis (PCA), partial least square-discriminant analysis (  ...  A B S T R A C T Raman spectroscopy was used on 95 samples comprising mainly of uranium ore concentrates as well as some UF 4 and UO 2 samples, in order to classify uranium compounds for nuclear forensic  ...  The support provided by the Australian Safeguards and Non-proliferation Office (ASNO) for the acquisition of samples from Australia is highly appreciated.  ... 
doi:10.1016/j.forsciint.2015.03.002 pmid:25863699 fatcat:ud6preglxbfvxomi7wwp5s5g2u

Multivariate analysis of BOLD activation patterns recovers graded depth representations in human visual and parietal cortex

Margaret Henderson, Vy Vo, Chaipat Chunharas, Thomas Sprague, John Serences
2019 eNeuro  
Past work has revealed that object position in two-dimensional (2D) retinotopic space is robustly represented in visual cortex and can be robustly predicted using a multivariate encoding model, in which  ...  However, no study to date has used an encoding model to estimate a representation of stimulus position in depth.  ...  *M.H. and V.V. authors contributed equally to this work. Acknowledgements: We thank Julie Golomb for helpful discussions and manifolds for dividing high-dimensional spaces into interpretable parts.  ... 
doi:10.1523/eneuro.0362-18.2019 pmid:31285275 pmcid:PMC6709213 fatcat:frlq7bqovrfuhpjzk6vf23eiy4

Contrasting visual working memory for verbal and non-verbal material with multivariate analysis of fMRI

Christian Habeck, Brian Rakitin, Jason Steffener, Yaakov Stern
2012 Brain Research  
Interestingly, subject expression of covariance patterns from both verbal and non-verbal retention phases correlated positively in the non-verbal task for all memory loads (p < 0.0001).  ...  Subsequently, the screen went blank for 7 s ('retention phase' or RET), and then displayed a probe stimulus for 3 s in which subjects indicated with a differential button press whether the probe was contained  ...  Results Behavioral performance Ordinal Trend Analysis in brain imaging data We performed Ordinal Trend Analysis (OrT CVA) on all task phases of both Letter and Shape tasks for the identification of  ... 
doi:10.1016/j.brainres.2012.05.045 pmid:22652306 pmcid:PMC3398171 fatcat:ogqtza6ysvgmjmim2wni2uzkqe
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