Integrating Multiple 3D Views through Frame-of-reference Interaction

Frame-of-reference interaction consists of a unified set of 3D interaction techniques for exploratory navigation of large virtual spaces in nonimmersive environments. It is based on a conceptual framework that considers navigation from a cognitive perspective, as a way of facilitating changes in user attention from one reference frame to another, rather than from the mechanical perspective of moving a camera between different points of interest. All of our techniques link multiple frames of reference in some meaningful way. Some techniques link multiple windows within a zooming environment while others allow seamless changes of user focus between static objects, moving objects, and groups of moving objects. We present our techniques as they are implemented in GeoZui3D, a geographic visualization system for ocean data

Frame of Reference Interaction.

We present a unified set of 3D interaction techniques that demonstrates an alternative way of thinking about the navigation of large virtual spaces in non-immersive environments. Our alternative conceptual framework views navigation from a cognitive perspective—as a way of facilitating changes in user attention from one reference frame to another—rather than from the mechanical perspective of moving a camera between different points of interest. All of our techniques link multiple frames of reference in some meaningful way. Some techniques link multiple windows within a zooming environment while others allow seamless changes of user attention between static objects, moving objects, and groups of moving objects. We present our techniques as they are implemented in GeoZui3D, a geographic visualization system for ocean dat

Haptic Interface for Center of Workspace Interaction

We build upon a new interaction style for 3D interfaces, called the center of workspace interaction. This style of interaction is defined with respect to a central fixed point in 3D space, conceptually within arm\u27s length of the user. For demonstration, we show a haptically enabled fish tank VR that utilizes a set of interaction widgets to support rapid navigation within a large virtual space. The fish tank VR refers to the creation of a small but high quality virtual reality that combines a number of technologies, such as head-tracking and stereo glasses, to their mutual advantag

On the Optimization of Visualizations of Complex Phenomena

The problem of perceptually optimizing complex visualizations is a difficult one, involving perceptual as well as aesthetic issues. In our experience, controlled experiments are quite limited in their ability to uncover interrelationships among visualization parameters, and thus may not be the most useful way to develop rules-of-thumb or theory to guide the production of high-quality visualizations. In this paper, we propose a new experimental approach to optimizing visualization quality that integrates some of the strong points of controlled experiments with methods more suited to investigating complex highly-coupled phenomena. We use human-in-the-loop experiments to search through visualization parameter space, generating large databases of rated visualization solutions. This is followed by data mining to extract results such as exemplar visualizations, guidelines for producing visualizations, and hypotheses about strategies leading to strong visualizations. The approach can easily address both perceptual and aesthetic concerns, and can handle complex parameter interactions. We suggest a genetic algorithm as a valuable way of guiding the human-in-the-loop search through visualization parameter space. We describe our methods for using clustering, histogramming, principal component analysis, and neural networks for data mining. The experimental approach is illustrated with a study of the problem of optimal texturing for viewing layered surfaces so that both surfaces are maximally observable

Single Photon Source with Individualized Single Photon Certifications

As currently implemented, single-photon sources cannot be made to produce single photons with high probability, while simultaneously suppressing the probability of yielding two or more photons. Because of this, single photon sources cannot really produce single photons on demand. We describe a multiplexed system that allows the probabilities of producing one and more photons to be adjusted independently, enabling a much better approximation of a source of single photons on demand. The scheme uses a heralded photon source based on parametric downconversion, but by effectively breaking the trigger detector area into multiple regions, we are able to extract more information about a heralded photon than is possible with a conventional arrangement. This scheme allows photons to be produced along with a quantitative ``certification'' that they are single photons. Some of the single-photon certifications can be significantly better than what is possible with conventional downconversion sources (using a unified trigger detector region), as well as being better than faint laser sources. With such a source of more tightly certified single photons, it should be possible to improve the maximum secure bit rate possible over a quantum cryptographic link. We present an analysis of the relative merits of this method over the conventional arrangement.Comment: 11 pages, 5 figures, SPIE Free-Space Laser Communication and Laser Imaging II. To appear in the proceeding of SPIE Free-Space Laser Communication and Laser Imaging II, vol 482

Panoramic Images for Situational Awareness in a 3D Chart-of-the-Future Display

Many early charts featured sketches of the coastline, providing a good picture of what the shore looked like from the bridge of a ship. These helped the mariner to distinguish one port from another during an approach and establish their rough position within that approach. More recent experimental 3D chart interfaces have incorporated 3D models of land topography and man-made structures to perform the same function. However, topography is typically captured from the air, by means of stereophotogrammetry or lidar and fails to present a good representation of what is seen from a vessel’s bridge. We have been conducting an investigation of ways to present photographic imagery to the mariner to better capture the utility of the early coastline sketches. Our focus has been on navigation in restricted waters, using the Piscataqua River as a test area. This is part of our “Chart-of-the-Future” project being conducted by The Data Visualization Research Lab at the UNH Center for Coastal and Ocean Mapping. Through our investigation, we have developed a new method for presenting photographic imagery to the mariner, in the form of a series of panoramic images progressing down the channel. The panoramas consist of images stitched almost seamlessly together into circular arcs, whose centers are intended to be close to the position of a vessel’s bridge during transit. When viewed from this center, there is no distortion, and distortion increases to a maximum between two panorama centers. Our preliminary trials suggest that panoramas can provide an excellent supplement to electronic navigation aids by making them visible in the context of what can be seen out the window. We believe panoramas will be especially useful both in familiarizing a mariner with an unfamiliar approach during planning, and in enhancing situational awareness at times of reduced visibility such as in fog, dusk, or nightfall

Bayesian models for syndrome- and gene-specific probabilities of novel variant pathogenicity

BACKGROUND: With the advent of affordable and comprehensive sequencing technologies, access to molecular genetics for clinical diagnostics and research applications is increasing. However, variant interpretation remains challenging, and tools that close the gap between data generation and data interpretation are urgently required. Here we present a transferable approach to help address the limitations in variant annotation. METHODS: We develop a network of Bayesian logistic regression models that integrate multiple lines of evidence to evaluate the probability that a rare variant is the cause of an individual's disease. We present models for genes causing inherited cardiac conditions, though the framework is transferable to other genes and syndromes. RESULTS: Our models report a probability of pathogenicity, rather than a categorisation into pathogenic or benign, which captures the inherent uncertainty of the prediction. We find that gene- and syndrome-specific models outperform genome-wide approaches, and that the integration of multiple lines of evidence performs better than individual predictors. The models are adaptable to incorporate new lines of evidence, and results can be combined with familial segregation data in a transparent and quantitative manner to further enhance predictions. Though the probability scale is continuous, and innately interpretable, performance summaries based on thresholds are useful for comparisons. Using a threshold probability of pathogenicity of 0.9, we obtain a positive predictive value of 0.999 and sensitivity of 0.76 for the classification of variants known to cause long QT syndrome over the three most important genes, which represents sufficient accuracy to inform clinical decision-making. A web tool APPRAISE [http://www.cardiodb.org/APPRAISE] provides access to these models and predictions. CONCLUSIONS: Our Bayesian framework provides a transparent, flexible and robust framework for the analysis and interpretation of rare genetic variants. Models tailored to specific genes outperform genome-wide approaches, and can be sufficiently accurate to inform clinical decision-making

Gramene

Grasses are one of the largest agricultural crops, providing food, industrial materials and renewable energy sources. Due to their large genome size and the number of the species in the taxa, many of the genomes are not targeted for complete sequencing. Gramene seeks to provide basic researchers, industry and educators with a resource that can be used as a tool for knowledge discovery across grass species. This chapter briefly outlines system requirements for end users and database hosting, outlines data types and basic navigation within Gramene and provides an example of how a maize researcher would use Gramene to leverage rice genome organization and phenotypic information to support targeted experimental research in maize