Jim X. Chen

A Model for Understanding How Virtual Reality Aids Complex Conceptual Learning

Designers and evaluators of immersive virtual reality systems have many ideas concerning how virtual reality can facilitate learning. However, we have little information concerning which of virtual realitys features provide the most leverage for enhancing understanding or how to customize those affordances for different learning environments. In part, this reflects the truly complex nature of learning. Features of a learning environment do not act in isolation; other factors such as the concepts or skills to be learned, individual characteristics, the learning experience, and the interaction experience all play a role in shaping the learning process and its outcomes. Through Project Science Space, we have been trying to identify, use, and evaluate immersive virtual realitys affordances as a means to facilitate the mastery of complex, abstract concepts. In doing so, we are beginning to understand the interplay between virtual realitys features and other important factors in shaping the learning process and learning outcomes for this type of material. In this paper, we present a general model that describes how we think these factors work together and discuss some of the lessons we are learning about virtual realitys affordances in the context of this model for complex conceptual learning.

Toward interactive-rate simulation of fluids with moving obstacles using Navier-Stokes equations

Abstract We present a new method for physically based modeling and interactive-rate simulation of 3D fluids in computer graphics. By solving the 2D Navier-Stokes equations using a computational fluid dynamics method, we map the surface into 3D using the corresponding pressures in the fluid flow field. The method achieves realistic interactive-rate fluid simulation by solving the physical governing laws of fluids but avoiding the extensive 3D fluid dynamics computation. Unlike previous computer graphics fluid models, our approach can simulate many different fluid behaviors by changing the internal or external boundary conditions. It can model different kinds of fluids by varying the Reynolds number. It can also simulate objects moving or floating in fluids. In addition, we can visualize the animation of the fluid flow field, the streakline of a flow field, and the blending of fluids of different colors. Our model can serve as a testbed to simulate many other fluid phenomena which have never been successfully modeled previously in computer graphics.

Real-time fluid simulation in a dynamic virtual environment

Simulating physically realistic complex fluid behaviors in a distributed interactive simulation (DIS) presents a challenging problem for computer graphics researchers. The authors consider how solving the 2D Navier-Stokes equations via a computational fluid dynamics method lets us map surfaces into 3D and achieves realistic real-time fluid surface behaviours.

Accurate Depth of Field Simulation in Real Time

We present a new post processing method of simulating depth of field based on accurate calculations of circles of confusion. Compared to previous work, our method derives actual scene depth information directly from the existing depth buffer, requires no specialized rendering passes, and allows easy integration into existing rendering applications. Our implementation uses an adaptive, two‐pass filter, producing a high quality depth of field effect that can be executed entirely on the GPU, taking advantage of the parallelism of modern graphics cards and permitting real time performance when applied to large numbers of pixels.

A model for team-based access control (TMAC 2004)

Role based access control (RBAC) has been proved to be effective for defining access control. However, in an environment where collaborative work is needed, additional features should be added on top of RBAC to accommodate the new requirements. In this paper we describe a team access control extension model called TMAC04 (Team-Based Access Control 2004), which is built on the well-known RBAC. The TMAC04 model efficiently represents teamwork in the real world. It allows certain users to join a team based on their existing roles in an organization within limited contexts and new permissions to perform the required work.

Real-time simulation of dust behavior generated by a fast traveling vehicle

Simulation of physically realistic complex dust behavior is very useful in training, education, art, advertising, and entertainment. There are no published models for real-time simulation of dust behavior generated by a traveling vehicle. In this paper, we use particle systems, computational fluid dynamics, and behavioral simulation techniques to simulate dust behavior in real time. First, we analyze the forces and factors that affect dust generation and the behavior after dust particles are generated. Then, we construct physically-based empirical models to generate dust particles and control the behavior accordingly. We further simplify the numerical calculations by dividing dust behavior into three stages, and establishing simplified particle system models for each stage. We employ motion blur, particle blending texture mapping, and other computer graphics techniques to achieve the final results. Our contributions include constructing physically-based empirical models to generate dust behavior and achieving simulation of the behavior in real time.

Advancing Interactive Visualization and Computational Steering

esearchers in scientific computation have the good R fortune to see their capabilities grow by more than an order of magnitude each decade. As high-end supercomputers have become more powerful, and what used to be called “supercomputing” performance has become available on the desktop, the scientific community has witnessed an explosion in its ability to generate results. Huge amounts of data are generated by computed simulations in engineering, chemistry, medicine, physics, and other areas. Additional vast data sets are coilected by sensing devices such as satellites, medical scanners, microscopes, radio telescopes, and geophysical sensors. Users, when presented with a new computed result or some other collection of on-line data, are impatient to see and understand it as quickly as possible. They often prefer to understand it from observing an image rather than from analyzing long lists of abstract numbers and symbols. Scientific visualization is a process of transforming the generated abstract data into meaningful visual form so that users can see and understand the results better and easier. Its goal is to make a system’s nature apparent at a glance. By necessity, systems that tightly couple high-performance computing to high-performance visualization are becoming more common, as are high-performance networks, which are beginning to allow remote visualization and interaction with running simulations. To introduce this theme section of IEEE CS&E we will touch briefly on some of the main methods and research issues in high-performance scientific visualization today. Two of the emerging visualization paradigms most useful to computational scientists are interactive vimalizatim and c m putational steering. We also present an example of an interactive application for studying fluid flow (see sidebar), showing how simulation and visualization can combine in real time for a better understanding of a phenomenon.

Data visualization: parallel coordinates and dimension reduction

Visualization techniques deal with multidimensional multivariable data sets. We introduce visualization methods for multidimensional data sets, including an effective dimension reduction method for the multivariate genetic algorithm data set.

Geographic statistics visualization: web-based linked micromap plots

Linked micromap (LM) plots offer a new template for displaying spatially indexed statistical summaries. One can use LM plots to visualize complex data in many areas. This paper introduces web-based interactive LM plots, a statistical data visualization system that integrates geographical data manipulation, visualization, interactive statistical graphics, and web-based Java technologies. The system effectively presents the complex and large-volume sample data of national cancer statistics of the United States.

Designing Computer Games to Teach Algorithms

Data structures and algorithms are important foundation topics in computer science education. However, they are often complex and hard to understand. Therefore, we introduce a new learning strategy that benefits from computer games’ popularity and engagement to help students understand algorithms better by designing computer games that visualize algorithms. To teach an algorithm, an educational computer game, namely an algorithm game, must have a game-play that simulates the behavior of the visualized algorithm and graphics depict the features of its data structure.