When humans talk with humans, they are able to use implicit situational information, or context, to increase the conversational bandwidth. This ability to use contextual information does not transfer well to human-com...
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ISBN:
(纸本)1581132484
When humans talk with humans, they are able to use implicit situational information, or context, to increase the conversational bandwidth. This ability to use contextual information does not transfer well to human-computer interaction. Part of the problem is the impoverished mechanisms for providing input to computers. Another aspect of the problem is that often we don't know what contextual information is relevant, useful, or even how to use it. However, by improving the computer's access to its context, we can increase the richness of communication in human-computer interaction and make it possible to produce more useful computational services.
High-Reynolds number turbulent incompressible multiphase flow represents a large class of engineering problems of key relevance to society. Here we describe our work on modeling two such problems: 1. The Consorcio de ...
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ISBN:
(纸本)9786188284401
High-Reynolds number turbulent incompressible multiphase flow represents a large class of engineering problems of key relevance to society. Here we describe our work on modeling two such problems: 1. The Consorcio de Aguas Bilbao Bizkaia is constructing a new storm tank system with an automatic cleaning system, based on periodically pushing tank water out in a tunnel 2. In the framework of the collaboration between BCAM - Basque center for Applied Mathematics and Tecnalia R & I, the interaction of the sea flow with a semi submersible floating offshore wind platform is computationally investigated. We study the MARIA' benchmark modeling breaking waves over objects in marine environments. Both of these problems are modeled in the the Direct FEM/General Galerkin methodology for turbulent incompressible variable-densitv flow 1,2 in the FEniCS software framework.
Importance. Medical images are essential for modern medicine and an important research subject in visualization. However,medical experts are often not aware of the many advanced three-dimensional (3D) medical image vi...
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Importance. Medical images are essential for modern medicine and an important research subject in visualization. However,medical experts are often not aware of the many advanced three-dimensional (3D) medical image visualization techniques thatcould increase their capabilities in data analysis and assist the decision-making process for specific medical problems. Ourpaper provides a review of 3D visualization techniques for medical images, intending to bridge the gap between medicalexperts and visualization researchers. Highlights. Fundamental visualization techniques are revisited for various medicalimaging modalities, from computational tomography to diffusion tensor imaging, featuring techniques that enhance spatialperception, which is critical for medical practices. The state-of-the-art of medical visualization is reviewed based on aprocedure-oriented classification of medical problems for studies of individuals and populations. This paper summarizes freesoftware tools for different modalities of medical images designed for various purposes, including visualization, analysis, andsegmentation, and it provides respective Internet links. Conclusions. visualization techniques are a useful tool for medicalexperts to tackle specific medical problems in their daily work. Our review provides a quick reference to such techniques giventhe medical problem and modalities of associated medical images. We summarize fundamental techniques and readily availablevisualization tools to help medical experts to better understand and utilize medical imaging data. This paper could contributeto the joint effort of the medical and visualization communities to advance precision medicine.
We present interactive techniques for identifying and extracting features in function fields. Function fields map points in n-dimensional Euclidean space to 1-dimensional scalar functions. Visual feature identificatio...
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Computer science as a discipline is failing to reach a diverse audience. As a result, computational illiteracy threatens many groups of underserved students - women, minorities and possibly other, as yet undocumented ...
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Computer science as a discipline is failing to reach a diverse audience. As a result, computational illiteracy threatens many groups of underserved students - women, minorities and possibly other, as yet undocumented groups, such as students of the humanities. If learning programming were contextualized in domains relevant to different audiences, more students would be motivated to learn to program. I contend that teaching computer science in the context of digital media manipulation will attract and engage many students who would otherwise not choose to learn programming.
作者：
Doug A. BowmanLarry F. HodgesGraphics
Visualization and Usability Center College of Computing Georgia Institute of Technology 801 Atlantic Drive
Atlanta GA and Graphics Visualization and Usability Center College of Computing Georgia Institute of Technology
We present a testbed for comparing predictive tracking algorithms that allows virtual environment system developers to make better choices about which predictors to use in their environments and aids researchers in de...
ISBN:
(纸本)9781581136869
We present a testbed for comparing predictive tracking algorithms that allows virtual environment system developers to make better choices about which predictors to use in their environments and aids researchers in determining how predictors work across various virtual environment configurations. Our testbed saves the virtual environment developer and researcher both time and effort with the important task of reducing dynamic tracking error and masking latency. The testbed consists of three components: a prediction algorithm library, a motion data repository, and a graphical testing application which provides users with the ability to test different predictive tracking algorithms across a variety of user motion sequences. The testbed provides enough generality for testing across different algorithmic and system parameters such as sampling rate, prediction time, and noise variance. The paper describes the contents of the predictor library and how to extend it, the types of motion data sets collected thus far, the motion data preparation methodology, and the graphical testing application's functionality and architecture. A simple testing scenario showing output from the testbed is also presented.
We present novel algorithms for predictive tracking of user position and orientation based on double exponential smoothing. These algorithms, when compared against Kalman and extended Kalman filter-based predictors wi...
ISBN:
(纸本)9781581136869
We present novel algorithms for predictive tracking of user position and orientation based on double exponential smoothing. These algorithms, when compared against Kalman and extended Kalman filter-based predictors with derivative free measurement models, run approximately 135 times faster with equivalent prediction performance and simpler implementations. This paper describes these algorithms in detail along with the Kalman and extended Kalman Filter predictors tested against. In addition, we describe the details of a predictor experiment and present empirical results supporting the validity of our claims that these predictors are faster, easier to implement, and perform equivalently to the Kalman and extended Kalman filtering predictors.
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