KWAN-LIU MA


PUBLICATIONS

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

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Hifocon: Object and Dimensional Coherence and Correlation in Multidimensional Visualization

Soon Tee Teoh and Kwan-Liu Ma

In Proceedings of International Symposium on Visual Computing
December, 2005, pp. 235-242

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In any multidimensional visualization, some information has to be compromised when projecting multidimensional data to two- or three-dimensional space. We introduce the concepts of dimensional and object coherence and correlation to analyze and classify multidimensional visualization techniques. These concepts are used as principles for our design of Hifocon, a new multidimensional data visualization system. ...

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A Hierarchical Graph-Based Segmentation Technique for High-Resolution Volume Data

Runzhen Huang and Kwan-Liu Ma

In Proceedings of International Symposium on Visual Computing
December, 2005, pp. 143-150

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We present a new hierarchical graph representation for volume data as well as its associated operations to enable interactive feature segmentation for high-resolution volume data. Our method constructs a low-resolution graph which represents a coarser resolution of the data. This graph enables the user to interactively sample and edit a feature of interest by drawing strokes on data slices. ...

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Intelligent Feature Extraction and Tracking for Visualizing Large-Scale 4D Flow Simulations (DVD Proceedings)

Fan-Yin Tzeng and Kwan-Liu Ma

In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC '05)
November, 2005

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Terascale simulations produce data that is vast in spatial, emporal, and variable domains, creating a formidable challenge for subsequent analysis. Feature extraction as a data reduction method offers a viable solution to this large data problem. This paper presents a new approach to the problem of extracting and visualizing 4D features within large volume data. Conventional methods requires either an analytical description of the feature of interest or tedious manual intervention throughout the feature extraction and tracking process ...

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A Visualization Methodology for Characterization of Network Scans

Chris Muelder, Kwan-Liu Ma, and Tony Bartoletti

In Proceedings of Workshop on Visualization for Computer Security (VizSEC2005)
October, 2005, pp. 29-38

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Many methods have been developed for monitoring network traffic, both using visualization and statistics. Most of these methods focus on the detection of suspicious or malicious activities. But what they often fail to do refine and exercise measures that contribute to the characterization of such activities and their sources, once they are detected. In particular, many tools exist that detect network scans or visualize them at a high level, but not very many tools exist that are capable of categorizing and analyzing network scans ...

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Opening the Black Box -- Data-Driven Visualization of Neural Network

Fan-Yin Tzeng and Kwan-Liu Ma

In Proceedings of Visualization 2005 Conference
October, 2005, pp. 383-390

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Artificial neural networks are computer software or hardware models inspired by the structure and behavior of neurons in the human nervous system. As a powerful learning tool, increasingly neural networks have been adopted by many large-scale information processing applications but there is no a set of well defined criteria for choosing a neural network. The user mostly treats a neural network as a black box and cannot explain how learning from input data was done nor how performance can be consistently ensured ...

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Interactive Visualization for Network and Port Scan Detection

Chris Muelder, Kwan-Liu Ma, and Tony Bartoletti

In Proceedings of the Eighth International Symposium on Recent Advances in Intrusion Detection (RAID 2005)
September, 2005, pp. 265-283

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Many times, network intrusion attempts begin with either a network scan, where a connection is attempted to every possible destination in a network, or a port scan, where a connection is attempted to each port on a given destination. Being able to detect such scans can help identify a more dangerous threat to a network. Several techniques exist to automatically detect scans, but these are mostly dependant on some threshold that an attacker could possibly avoid crossing ...

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Expressive Line Selection by Example

Eric Lum and Kwan-Liu Ma

The Visual Computer (Proceedings of Pacific Graphics 2005 Conference)
Volume 21, Number 8, September, 2005, pp. 811-820

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An important problem in computer generated line drawing is determining which set of lines produces a representation that is in agreement with a user’s communication goals. We describe a method that enables a user to intuitively specify which types of lines should appear in rendered images. Our method employs conventional silhouette-edge and other feature-line extraction algorithms to derive a set of candidate lines, and integrates machine learning into a user-directed line removal process using a sketching metaphor ...

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High Quality Rendering of Compressed Volume Data Formats

Nathaniel Fout, Hiroshi Akiba, Kwan-Liu Ma, Aaron Lefohn, and Joe Kniss

In Proceedings of Eurographics /IEEE-VGTC Symposium on Visualization
June, 2005, pp. 77-84

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Rendering directly from packed or compressed volume data formats using graphics hardware has advantages in terms of memory consumption and bandwidth, but results in lower-quality images due to the prohibitive cost of performing interpolation and gradient-based shading on the reconstructed data. The problem with the existing method lies in its close coupling of decompression and interpolation. We demonstrate that deferred filtering overcomes this problem by using a two-pass decompression and rendering strategy ...

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Performing BGP Experiments on a Semi-Realistic Internet Tesbed Environment

Ke Zhang, Soon Tee Teoh, Shih Ming Tzeng, Rattapon Limprasittipom, S. Felix Wu, Chen-Nee Chuah, and Kwan-Liu Ma

In Proceedings of the Third International Workshop on Security in Distributed Computing Systems
June, 2005, pp. 130-136

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We have built a router testbed that is connected to the Deter/Emist experimental infrastructure. Our goal is to create a semi-realistic testbed to conduct BGP experiments, measure and visualize their impact on network performance and stability. Such testbed is also useful for evaluating different security countermeasures. Our testbed architecture includes four components: routing topology, background traffic, data analysis and visualization. This paper describes how we launch two specific BGP attacks, (a) Multiple Origin AS and (b) route flap damping attacks, and the lessons learned ...

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End-to-end Data Reduction and Hardware Accelerated Rendering Techniques for Visualizing Time-Varying Non-uniform Grid Volume Data

Hiroshi Akiba, Kwan-Liu Ma, and John Clyne

In Proceedings of the International Workshop on Volume Graphics
June, 2005, pp. 31-39

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We present a systematic approach for direct volume rendering terascale-sized data that are time-varying, and possibly non-uniformly sampled, using only a single commodity graphics PC. Our method employs a data reduction scheme that combines lossless, wavelet-based progressive data access with a user-directed, hardware-accelerated data packing technique. Data packing is achieved by discarding data blocks with values outside the data interval of interest and encoding the remaining data in a structure that can be ef ciently decoded in the GPU ...

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Scientific Discovery through Advanced Visualization

Kwan-Liu Ma, Eric Lum, Hongfeng Yu, Hiroshi Akiba, Min-Yu Huang, and Yue Wang

Journal of Physics
Volume 16, June, 2005, pp. 491-500

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The SciDAC program of the Department of Energy has brought together tremendous scientific expertises and computing resources to realize the promise of terascale computing for attempting to answer some of the most important basic science questions. Scientific visualization is an indispensable path to gleaning insight from the massive data produced by terascale simulations. Unless the visualization challenges presented by the terascale simulations be adequately addressed, the value of conducting these immense and costly simulations is not being fully realized ...

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An Intelligent System Approach to Higher-Dimensional Classification of Volume Data

Fan-Yin Tzeng, Eric Lum, and Kwan-Liu Ma

IEEE Transactions on Visualization and Computer Graphics
Volume 11, Number 3, May/June, 2005, pp. 273-284

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In volume data visualization, the classification step is used to determine voxel visibility and is usually carried out through the interactive editing of a transfer function that defines a mapping between voxel value and color/opacity. This approach is limited by the difficulties in working effectively in the transfer function space beyond two dimensions. We present a new approach to the volume classification problem which couples machine learning and a painting metaphor to allow more sophisticated classification in an intuitive manner ...

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Calculating Hierarchical Radiosity Form Factors Using Programmable Graphics Hardware

Eric Lum, Kwan-Liu Ma, and Nelson Max

Journal of Graphics Tools
Volume 10, Number 4, May, 2005, pp. 61-71

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We present a method for the efficient calculation of ultiresolution radiosity for factors using programmable graphics hardware. Mipmapped ID textures are used t allow for highly refined patches with the mipmapping mechanism working as a hardware-accelerated oracle for the dynamic linking of patch hierarchies. The actual form facto values for unoccluded patches are then computed with the analytic differential area t polygon form factor using programmable graphics hardware ...

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Time-Varying Multivariate Volume Data Reduction

Nathan Fout, Kwan-Liu Ma, and James Ahrens

In Proceedings of ACM Symposium on Applied Computing
March, 2005, pp. 1224-1230

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Large-scale supercomputing is revolutionizing the way science is conducted. A growing challenge, however, is understanding the massive quantities of data produced by large-scale simulations. The data, typically time-varying, multivariate, and volumetric, can occupy from hundreds of gigabytes to several terabytes of storage space. Transferring and processing volume data of such sizes is prohibitively expensive and resource intensive. Although it may not be possible to entirely alleviate these problems, data compression should be considered as part of a viable solution, especially when the primary means of data analysis is volume rendering ...

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Discovering Parametric Clusters in Social Small-World Graphs

Johnathan McPherson, Kwan-Liu Ma, and Michael Ogawa

In Proceedings of ACM Symposium on Applied Computing
March, 2005, pp. 1231-1238

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We present a strategy for analyzing large, social small-world graphs, such as those formed by human networks. Our approach brings together ideas from a number of different research areas, including graph layout, graph clustering and partitioning, machine learning, and user interface design. It helps users explore the networks and develop insights concerning their members and structure that may be difficult or impossible to discover via traditional means, including existing graph visualization and/or statistical methods ...

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A Study of I/O Techniques for Parallel Visualization

Hongfeng Yu and Kwan-Liu Ma

Journal of Parallel Computing
Volume 31, Number 2, February, 2005, pp. 167-183

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This paper presents two parallel I/O methods for the visualization of time-varying volume data in a high-performance computing environment. We discuss the interplay between the parallel renderer, I/O strategy, and file system, and show the results of our study on the performance of the I/O strategies with and without MPI parallel I/O support. The targeted application is earthquake modeling using a large 3D unstructured mesh consisting of one hundred millions cells ...