Yun Jang - Academia.edu (original) (raw)
Papers by Yun Jang
Coordinated animal-human health monitoring can provide an early warning system with fewer false a... more Coordinated animal-human health monitoring can provide an early warning system with fewer false alarms for naturally occurring disease outbreaks, as well as biological, chemical and environmental incidents. This monitoring requires the integration and analysis of multi-field, multi-scale and multi-source data sets. In order to better understand these data sets, models and measurements at different resolutions must be analyzed. To facilitate these investigations, we have created an application to provide a visual analytics framework for analyzing both human emergency room data and veterinary hospital data. Our integrated visual analytic tool links temporally varying geospatial visualization of animal and human patient health information with advanced statistical analysis of these multi-source data. Various statistical analysis techniques have been applied in conjunction with a spatio-temporal viewing window. Such an application provides researchers with the ability to visually search the data for clusters in both a statistical model view and a spatio-temporal view. Our interface provides a factor specification/filtering component to allow exploration of causal factors and spread patterns. In this paper, we will discuss the application of our linked animal-human visual analytics (LAHVA) tool to two specific case studies. The first case study is the effect of seasonal influenza and its correlation with different companion animals (e.g., cats, dogs) syndromes. Here we use data from the Indiana Network for Patient Care (INPC) and Banfield Pet Hospitals in an attempt to determine if there are correlations between respiratory syndromes representing the onset of seasonal influenza in humans and general respiratory syndromes in cats and dogs. Our second case study examines the effect of the release of industrial wastewater in a community through companion animal surveillance.
Computer Graphics Forum, 2006
Functional approximation of scattered data is a popular technique for compactly representing vari... more Functional approximation of scattered data is a popular technique for compactly representing various types of datasets in computer graphics, including surface, volume, and vector datasets. Typically, sums of Gaussians or similar radial basis functions are used in the functional approximation and PC graphics hardware is used to quickly evaluate and render these datasets. Previously, researchers presented techniques for spatially-limited spherical Gaussian radial basis function encoding and visualization of volumetric scalar, vector, and multifield datasets. While truncated radially symmetric basis functions are quick to evaluate and simple for encoding optimization, they are not the most appropriate choice for data that is not radially symmetric and are especially problematic for representing linear, planar, and many non-spherical structures. Therefore, we have developed a volumetric approximation and visualization system using ellipsoidal Gaussian functions which provides greater compression, and visually more accurate encodings of volumetric scattered datasets. In this paper, we extend previous work to use ellipsoidal Gaussians as basis functions, create a rendering system to adapt these basis functions to graphics hardware rendering, and evaluate the encoding effectiveness and performance for both spherical Gaussians and ellipsoidal Gaussians.
Figure 1: RBF reconstruction of unstructured CFD data. (a) Volume rendering of 1,943,383 tetrahed... more Figure 1: RBF reconstruction of unstructured CFD data. (a) Volume rendering of 1,943,383 tetrahedral shock data set using 2,932 RBF functions. (b) Volume rendering of a 156,642 tetrahedral oil reservoir data set using 222 RBF functions organized in a hierarchy of 49 cells.
Mobile devices are rapidly gaining popularity due to their small size and their wide range of fun... more Mobile devices are rapidly gaining popularity due to their small size and their wide range of functionality. With the constant improvement in wireless network access, they are an attractive option not only for day to day use. but also for in-field analytics by first responders in widespread areas. However, their limited processing, display, graphics and power resources pose a major challenge in developing effective applications. Nevertheless, they are vital for rapid decision making in emergencies when combined with appropriate analysis tools. In this paper, we present an efficient, interactive visual analytic system using a PDA to visualize network information from Purdue's Ross-Ade Stadium during football games as an example of in-held data analytics combined with text and video analysis. With our system, we can monitor the distribution of attendees with mobile devices throughout the stadium through their access of information and association/disassociation from wireless access points, enabling the detection of crowd movement and event activity. Through correlative visualization and analysis of synchronized video (instant replay video) and text information (play statistics) with the network activity, we can provide insightful information to network monitoring personnel, safety personnel and analysts. This work provides a demonstration and testbed for mobile sensor analytics that will help to improve network performance and provide safety personnel with information for better emergency planning and guidance
IEEE Computer Graphics and Applications, 2005
: Four visualizations of RBF encoded datasets. Left image: Interactively extracted and volume ren... more : Four visualizations of RBF encoded datasets. Left image: Interactively extracted and volume rendered vorticity from the Tornado dataset encoded with 2,100 RBFs. Second: Traces of 110 particles tracked in experimentally obtained Channel dataset encoded with 2,105 RBFs. Third image: Volume rendering of water pressure for an injection well. The 156,642 tetrahedra dataset of a simulated black-oil reservoir is encoded using 141 RBFs. Fourth image: Isosurface rendering of vorticity magnitude. Positive helicity has been mapped to red colors and negative helicity to blue colors.
Using mobile devices for visualization provides a ubiquitous environment for accessing informatio... more Using mobile devices for visualization provides a ubiquitous environment for accessing information and effective decision making. These visualizations are critical in satisfying the knowledge needs of operators in areas as diverse as education, business, law enforcement, protective services, medical services, scientific discovery, and homeland security. In this paper, we present an efficient and interactive mobile visual analytic system for increased situational awareness and decision making in emergency response and training situations. Our system provides visual analytics with locational scene data within a simple interface tailored to mobile device capabilities. In particular, we focus on processing and displaying sensor network data for first responders. To verify our system, we have used simulated data of The Station nightclub fire evacuation.
a) (b) (c) (d) Figure 1: Examples of oriented structural flow visualizations harnessing the effec... more a) (b) (c) (d) Figure 1: Examples of oriented structural flow visualizations harnessing the effectiveness of illustrative and photographic flow techniques. (a) is an illustrative drawing of temperature advection in a convection dataset. The left half shows a normal volume rendering while the right half shows a contour volume rendering using a da Vinci-inspired color palette. (b) emulates a color-pencil sketch to visualize shear stress in a Y-pipe. (c) shows the bow shock of flow past the X38 spacecraft created from a volumetric Schlieren visualization, while (d) shows the flow and tail fin vortices visualized using a volumetric shadowgraph.
Coordinated animal-human health monitoring can provide an early warning system with fewer false a... more Coordinated animal-human health monitoring can provide an early warning system with fewer false alarms for naturally occurring disease outbreaks, as well as biological, chemical and environmental incidents. This monitoring requires the integration and analysis of multi-field, multi-scale and multi-source data sets. In order to better understand these data sets, models and measurements at different resolutions must be analyzed. To facilitate these investigations, we have created an application to provide a visual analytics framework for analyzing both human emergency room data and veterinary hospital data. Our integrated visual analytic tool links temporally varying geospatial visualization of animal and human patient health information with advanced statistical analysis of these multi-source data. Various statistical analysis techniques have been applied in conjunction with a spatio-temporal viewing window. Such an application provides researchers with the ability to visually search the data for clusters in both a statistical model view and a spatio-temporal view. Our interface provides a factor specification/filtering component to allow exploration of causal factors and spread patterns. In this paper, we will discuss the application of our linked animal-human visual analytics (LAHVA) tool to two specific case studies. The first case study is the effect of seasonal influenza and its correlation with different companion animals (e.g., cats, dogs) syndromes. Here we use data from the Indiana Network for Patient Care (INPC) and Banfield Pet Hospitals in an attempt to determine if there are correlations between respiratory syndromes representing the onset of seasonal influenza in humans and general respiratory syndromes in cats and dogs. Our second case study examines the effect of the release of industrial wastewater in a community through companion animal surveillance.
Computer Graphics Forum, 2006
Functional approximation of scattered data is a popular technique for compactly representing vari... more Functional approximation of scattered data is a popular technique for compactly representing various types of datasets in computer graphics, including surface, volume, and vector datasets. Typically, sums of Gaussians or similar radial basis functions are used in the functional approximation and PC graphics hardware is used to quickly evaluate and render these datasets. Previously, researchers presented techniques for spatially-limited spherical Gaussian radial basis function encoding and visualization of volumetric scalar, vector, and multifield datasets. While truncated radially symmetric basis functions are quick to evaluate and simple for encoding optimization, they are not the most appropriate choice for data that is not radially symmetric and are especially problematic for representing linear, planar, and many non-spherical structures. Therefore, we have developed a volumetric approximation and visualization system using ellipsoidal Gaussian functions which provides greater compression, and visually more accurate encodings of volumetric scattered datasets. In this paper, we extend previous work to use ellipsoidal Gaussians as basis functions, create a rendering system to adapt these basis functions to graphics hardware rendering, and evaluate the encoding effectiveness and performance for both spherical Gaussians and ellipsoidal Gaussians.
Figure 1: RBF reconstruction of unstructured CFD data. (a) Volume rendering of 1,943,383 tetrahed... more Figure 1: RBF reconstruction of unstructured CFD data. (a) Volume rendering of 1,943,383 tetrahedral shock data set using 2,932 RBF functions. (b) Volume rendering of a 156,642 tetrahedral oil reservoir data set using 222 RBF functions organized in a hierarchy of 49 cells.
Mobile devices are rapidly gaining popularity due to their small size and their wide range of fun... more Mobile devices are rapidly gaining popularity due to their small size and their wide range of functionality. With the constant improvement in wireless network access, they are an attractive option not only for day to day use. but also for in-field analytics by first responders in widespread areas. However, their limited processing, display, graphics and power resources pose a major challenge in developing effective applications. Nevertheless, they are vital for rapid decision making in emergencies when combined with appropriate analysis tools. In this paper, we present an efficient, interactive visual analytic system using a PDA to visualize network information from Purdue's Ross-Ade Stadium during football games as an example of in-held data analytics combined with text and video analysis. With our system, we can monitor the distribution of attendees with mobile devices throughout the stadium through their access of information and association/disassociation from wireless access points, enabling the detection of crowd movement and event activity. Through correlative visualization and analysis of synchronized video (instant replay video) and text information (play statistics) with the network activity, we can provide insightful information to network monitoring personnel, safety personnel and analysts. This work provides a demonstration and testbed for mobile sensor analytics that will help to improve network performance and provide safety personnel with information for better emergency planning and guidance
IEEE Computer Graphics and Applications, 2005
: Four visualizations of RBF encoded datasets. Left image: Interactively extracted and volume ren... more : Four visualizations of RBF encoded datasets. Left image: Interactively extracted and volume rendered vorticity from the Tornado dataset encoded with 2,100 RBFs. Second: Traces of 110 particles tracked in experimentally obtained Channel dataset encoded with 2,105 RBFs. Third image: Volume rendering of water pressure for an injection well. The 156,642 tetrahedra dataset of a simulated black-oil reservoir is encoded using 141 RBFs. Fourth image: Isosurface rendering of vorticity magnitude. Positive helicity has been mapped to red colors and negative helicity to blue colors.
Using mobile devices for visualization provides a ubiquitous environment for accessing informatio... more Using mobile devices for visualization provides a ubiquitous environment for accessing information and effective decision making. These visualizations are critical in satisfying the knowledge needs of operators in areas as diverse as education, business, law enforcement, protective services, medical services, scientific discovery, and homeland security. In this paper, we present an efficient and interactive mobile visual analytic system for increased situational awareness and decision making in emergency response and training situations. Our system provides visual analytics with locational scene data within a simple interface tailored to mobile device capabilities. In particular, we focus on processing and displaying sensor network data for first responders. To verify our system, we have used simulated data of The Station nightclub fire evacuation.
a) (b) (c) (d) Figure 1: Examples of oriented structural flow visualizations harnessing the effec... more a) (b) (c) (d) Figure 1: Examples of oriented structural flow visualizations harnessing the effectiveness of illustrative and photographic flow techniques. (a) is an illustrative drawing of temperature advection in a convection dataset. The left half shows a normal volume rendering while the right half shows a contour volume rendering using a da Vinci-inspired color palette. (b) emulates a color-pencil sketch to visualize shear stress in a Y-pipe. (c) shows the bow shock of flow past the X38 spacecraft created from a volumetric Schlieren visualization, while (d) shows the flow and tail fin vortices visualized using a volumetric shadowgraph.