KWAN-LIU MA


PUBLICATIONS

(A more complete list can be seen at DBLP.)

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Visualizing 3D Earthquake Simulation Data

Cheng-Kai Chen, Chris Ho, Carlos Correa, Kwan-Liu Ma, and Ahmed Elgamal

IEEE Computing in Science and Engineering
Volume 13, Number 6, 2011, pp. 52-63

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As exemplified in a state-of-the-art bridge-foundation-ground model simulation, a suite of new visualization techniques let scientists study seismic waves and interactively investigate and explore their data. In so doing, the techniques further scientific understanding and thus facilitate the development of new methods to protect real-world infrastructures against otherwise devastating earthquakes. ...

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A Rendering Framework for Multiscale Views of 3D Models

Wei-Hsien Hsu, Kwan-Liu Ma, and Carlos Correa

ACM Transactions on Graphics
(Accepted for publication and presentation by ACM SIGGRAPH Asia 2011 Conference)
Volume 30, Number 6, December, 2011

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Images that seamlessly combine views at different levels of detail are appealing. However, creating such multiscale images is not a trivial task, and most such illustrations are handcrafted by skilled
artists. This paper presents a framework for direct multiscale rendering of geometric and volumetric models. The basis of our approach is a set of non-linearly bent camera rays that smoothly cast through multiple scales. ...

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Collaborative Visualization: Definition, Challenges, and Research Agenda

Petra Isenberg, Niklas Elmqvist, Jean Scholtz, Daniel Cernea, Kwan-Liu Ma, and Hans Hagen

Information Visualization Journal (IVS)
(Special Issue on Information Visualization: State of the Field and New Research Directions)
Volume 10, Number 4, October, 2011, pp. 310-326

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The conflux of two growing areas of technology— collaboration and visualization—into a new research direction, collaborative visualization, provides new re- search challenges. Technology now allows us to eas- ily connect and collaborate with one another—in set- tings as diverse as over networked computers, across mobile devices, or using shared displays such as inter- active walls and tabletop surfaces. Digital information is now regularly accessed by multiple people in order to share information, to view it together, to analyze it, or to form decisions ...

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EVEVis: A Multi-Scale Visualization System for Dense Evolutionary Data

Robert Miller, Vadim Mozhayskiy, Ilias Tagkopoulos, and Kwan-Liu Ma

In Proceedings of BioVis
(accepted for publication and presentation)
October, 2011

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Evolutionary simulations can produce datasets of thousands or millions of separate entities, complete with their genealogical relationships. Biologists must examine this data to determine when and where these entities have changed, both on an individual basis and on a population-wide basis. Therefore, desirable features of a visualization system for evolutionary data are the capability of showing the status of the population at any given moment in time, good scalability, and smooth transition between high-level and low-level views. ...

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Parallel Clustering for Visualizing Large Scientific Line Data

Jishang Wei, Hongfeng Yu, and Kwan-Liu Ma

In Proceedings of IEEE Symposium on Large Data Analysis and Visualization (LDAV)
(Accepted for presentation and publication)
October, 2011

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In this paper, we present a parallel design of regression model-based clustering to categorize and visualize large line data derived from detailed scientific simula- tions by leveraging the power of heterogeneous systems. This par- allel clustering method employs the Expectation Maximization al- gorithm to iteratively approach an optimal data partition result. We introduce a sorted-balance algorithm to partition and distribute the lines with various lengths among multiple computing nodes ...

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An Illustrative Visualization Framework for 3D Vector Fields

Cheng-Kai Chen, Shi Yan, Hongfeng Yu, Nelson Max, and Kwan-Liu Ma

Computer Graphics Forum
(Also as Pacific Graphics 2011 Conference Proceedings; acceptance rate 16%)
September, 2011

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Most 3D vector field visualization techniques suffer from the problem of visual clutter, and it remains a challenging task to effectively convey both directional and structural information of 3D vector fields. In this paper, we present a novel visualization framework that combines the advantages of clustering methods and illustrative rendering techniques to generate a concise and informative depiction of complex flow structures ...

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Graph-Based Fire Synthesis

Yubo Zhang, Carlos Correa, and Kwan-Liu Ma

In Proceedings of ACM/Eurographics Symposium on Computer Animation (SCA 2011)
(accepted for publication and presentation)
August, 2011

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We present a novel graph-based data-driven technique for cost-effective fire modeling. This technique allows composing long animation sequences using a few short simulations. Motivated by the motion graph technique used in character animations, we introduce a new type of graph which can be applied to creating fire phenomena. Each graph node consists of a group of flow particle pathlines instead of a set of volumetric state fields. ...

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TVi: A Visual Querying System for Network Monitoring and Anomaly Detection

Alberto Boschetti, Chris Muelder, Luca Salgarelli, and Kwan-Liu Ma

In Proceedings of VizSec 2011
July, 2011

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Monitoring, anomaly detection and forensics are essential tasks that must be carried out routinely for every computer network. The sheer volume of data generated by conven- tional anomaly detection tools such as Snort often makes it difficult to explain the nature of an attack and track down its source. In this paper we present TVi, a tool that com- bines multiple visual representations of network traces care- fully designed and tightly coupled to support different levels of visual-based querying and reasoning required for mak- ing sense of complex traffic data ...

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Semantic-Preserving Word Cloud Generation by Seam Carving

Yingcai Wu, Thomas Provan, Shixia Liu, Furu Wei, and Kwan-Liu Ma

Computer Graphics Forum
(EuroVis 2011)
Volume 30, Number 3, June, 2011

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Word clouds are proliferating on Internet and have received much attention in visual analytics. Although word clouds can help users understand the major content of a document collection quickly, their capability for visu- ally comparing documents is limited, as the words are often arranged randomly or in alphabetical order, so the stability is not well maintained among different word clouds. To tackle this problem, we propose a new method to create semantic-preserving word clouds for comparative visualization, by leveraging tailored seam carving, a well-established content-aware image resizing operator ...

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Visual Recommendations for Network Navigation

Tarik Crnovrsanin, Isaac Liao, Yingcai Wu, and Kwan-Liu Ma

Computer Graphics Forum
(EuroVis 2011)
Volume 30, Number 3, June, 2011

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Understanding large, complex networks is important for many critical tasks, including decision making, process optimization, and threat detection. Existing network analysis tools often lack intuitive interfaces to support the exploration of large scale data. We present a visual recommendation system to help guide users during navi- gation of network data. Collaborative filtering, similarity metrics, and relative importance are used to generate recommendations of potentially significant nodes for users to explore ...

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Visual Analysis of I/O System Behavior for High-End Computing

Chris Muelder, Carmen Sigovan, Kwan-Liu Ma, Jason Cope, Sam Lang, Kamil Iskra, Pete Beckman, and Robert Ross

In Proceedings of 3rd Workshop on Large-Scale System and Application Performance (LSAP), HDPC 2011
(Best paper award)
ACM, June, 2011

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As supercomputers grow ever larger, so too do the size of the sim- ulations run on them and the size of the data they read from and output to large scale parallel file systems. The operational patterns of modern parallel I/O systems are far too complex to allow for a direct analysis of their trace logs. Several visualization methods have been developed to address this issue ...

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Visualizing Social Networks

Carlos Correa and Kwan-Liu Ma

Springer
Chapter 11: pp. 307-326 Social Network Data Analytics, 2011

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With today‘s ubiquity and popularity of social network applications, the abil- ity to analyze and understand large networks in an ef␣cient manner becomes critically important. However, as networks become larger and more complex, reasoning about social dynamics via simple statistics is not a feasible option. To overcome these limitations, we can rely on visual metaphors. Visualization nowadays is no longer a passive process that produces images from a set of num- bers ...

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A Preview and Exploratory Technique for Large-Scale Scientific Simulations

Anna Tikhonova, Hongfeng Yu, Carlos D. Correa, Jacqueline H. Chen, and Kwan-Liu Ma

In Proceedings of Eurographics Parallel Graphics and Visualization Symposium (EGPGV)
(Accepted for publication)
April, 2011

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Successful in-situ and remote visualization solutions must have minimal storage requirements and account for only a small percentage of supercomputing time. One solution that meets these requirements is to store a compact intermediate representation of the data, instead of a 3D volume itself. Recent work explores the use of attenuation functions as a data representation that summarizes the distribution of attenuation along the rays ...

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A Comparison of Gradient Estimation Methods for Volume Rendering on Unstructured Meshes

Carlos Correa, Robert Hero, and Kwan-Liu Ma

IEEE Transactions on Visualization and Computer Graphics
Volume 17, Number 3, March, 2011, pp. 305-319

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This paper presents a study of gradient estimation methods for rendering unstructured-mesh volume data. Gradient estimation is necessary for rendering shaded isosurfaces and specular highlights, which provide important cues for shape and depth. Gradient estimation has been widely studied and deployed for regular-grid volume data to achieve local illumination effects, but has been, otherwise, for unstructured-mesh data. As a result, most of the unstructured-mesh volume visualizations made so far were unlit ...

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Static Correlation Visualization for Large Time-Varying Volume Data

Cheng-Kai Chen, Chaoli Wang, Kwan-Liu Ma, and Andrew Wittenberg

In Proceedings of IEEE Pacific Visualization Symposium
March, 2011, pp. 27-34

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Finding correlations among data is one of the most essential tasks in many scientific investigations and discoveries. This paper addresses the issue of creating a static volume classification that summarizes the correlation connection in time-varying multivariate data sets. In practice, computing all temporal and spatial correlations for large 3D time-varying multivariate data sets is prohibitively expensive. We present a sampling-based approach to classifying correlation patterns ...

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Analyzing Information Transfer in Time-Varying Multivariate Data

Chaoli Wang, Hongfeng Yu, Ray W. Grout, Kwan-Liu Ma, and Jacqueline H. Chen

In Proceedings of IEEE Pacific Visualization Symposium
March, 2011, pp. 99-106

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Effective analysis and visualization of time-varying multivariate data is crucial for understanding complex and dynamic variable in- teraction and temporal evolution. Advances made in this area are mainly on query-driven visualization and correlation exploration. Solutions and techniques that investigate the important aspect of causal relationships among variables have not been sought. In this paper, we present a new approach to analyzing and visualizing time- varying multivariate volumetric and particle data sets through the study of information flow using the information-theoretic concept of transfer entropy ...

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Dual space analysis of turbulent combustion particle data

Jishang Wei, Hongfeng Yu, Ray W. Grout, Jacqueline H. Ma, and Kwan-Liu Ma

In Proceedings of IEEE Pacific Visualization Symposium
March, 2011, pp. 91-98

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Current simulations of turbulent flames are instrumented with particles to capture the dynamic behavior of combustion in next-generation engines. Categorizing the set of many millions of particles, each of which is featured with a history of its movement positions and changing thermo-chemical states, helps understand the turbulence mechanism. We introduce a dual-space method to analyze such data, starting by clustering the time series curves in the phase space of the data, and then visualizing the corresponding trajectories of each cluster in the physical space ...

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Feature-Preserving Volume Data Reduction and Focus+Context Visualization

Yu-Shuen Wang, Chaoli Wang, Tong-Yee Lee, and Kwan-Liu Ma

IEEE Transactions on Visualization and Computer Graphics
Volume 17, Number 2, February, 2011, pp. 171-181

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The growing sizes of volumetric data sets pose a great challenge for interactive visualization. In this paper, we present a feature-preserving data reduction and focus+context visualization method based on transfer function driven, continuous voxel repositioning and resampling techniques. Rendering reduced data can enhance interactivity. Focus+context visualization can show details of selected features in context on display devices with limited resolution. Our method utilizes the input transfer function to assign importance values to regularly partitioned regions of the volume data ...

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Visibility Histograms and Visibility-Driven Transfer Function

Carlos Correa and Kwan-Liu Ma

IEEE Transactions on Visualization and Computer Graphics
Volume 17, Number 2, February, 2011, pp. 192-204

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Direct volume rendering is an important tool for visualizing complex data sets. However, in the process of generating 2D images from 3D data, information is lost in the form of attenuation and occlusion. The lack of a feedback mechanism to quantify the loss of information in the rendering process makes the design of good transfer functions a difficult and time consuming task ...