Spatial Text Visualization Using Automatic Typographic Maps.

We present a method for automatically building typographic maps that merge text and spatial data into a visual representation where text alone forms the graphical features. We further show how to use this approach to visualize spatial data such as traffic density, crime rate, or demographic data. The technique accepts a vector representation of a geographic map and spatializes the textual labels in the space onto polylines and polygons based on user-defined visual attributes and constraints. Our sample implementation runs as a Web service, spatializing shape files from the OpenStreetMap project into typographic maps for any region.

Forecasting Hotspots-A Predictive Analytics Approach.

Current visual analytics systems provide users with the means to explore trends in their data. Linked views and interactive displays provide insight into correlations among people, events, and places in space and time. Analysts search for events of interest through statistical tools linked to visual displays, drill down into the data, and form hypotheses based upon the available information. However, current systems stop short of predicting events. In spatiotemporal data, analysts are searching for regions of space and time with unusually high incidences of events (hotspots). In the cases where hotspots are found, analysts would like to predict how these regions may grow in order to plan resource allocation and preventative measures. Furthermore, analysts would also like to predict where future hotspots may occur. To facilitate such forecasting, we have created a predictive visual analytics toolkit that provides analysts with linked spatiotemporal and statistical analytic views. Our system models spatiotemporal events through the combination of kernel density estimation for event distribution and seasonal trend decomposition by loess smoothing for temporal predictions. We provide analysts with estimates of error in our modeling, along with spatial and temporal alerts to indicate the occurrence of statistically significant hotspots. Spatial data are distributed based on a modeling of previous event locations, thereby maintaining a temporal coherence with past events. Such tools allow analysts to perform real-time hypothesis testing, plan intervention strategies, and allocate resources to correspond to perceived threats.

Use of technology in children's dietary assessment.

BACKGROUND: Information on dietary intake provides some of the most valuable insights for mounting intervention programmes for the prevention of chronic diseases. With the growing concern about adolescent overweight, the need to accurately measure diet becomes imperative. Assessment among adolescents is problematic as this group has irregular eating patterns and they have less enthusiasm for recording food intake. SUBJECTS/METHODS: We used qualitative and quantitative techniques among adolescents to assess their preferences for dietary assessment methods. RESULTS: Dietary assessment methods using technology, for example, a personal digital assistant (PDA) or a disposable camera, were preferred over the pen and paper food record. CONCLUSIONS: There was a strong preference for using methods that incorporate technology such as capturing images of food. This suggests that for adolescents, dietary methods that incorporate technology may improve cooperation and accuracy. Current computing technology includes higher resolution images, improved memory capacity and faster processors that allow small mobile devices to process information not previously possible. Our goal is to develop, implement and evaluate a mobile device (for example, PDA, mobile phone) food record that will translate to an accurate account of daily food and nutrient intake among adolescents. This mobile computing device will include digital images, a nutrient database and image analysis for identification and quantification of food consumption. Mobile computing devices provide a unique vehicle for collecting dietary information that reduces the burden on record keepers. Images of food can be marked with a variety of input methods that link the item for image processing and analysis to estimate the amount of food. Images before and after the foods are eaten can estimate the amount of food consumed. The initial stages and potential of this project will be described.

Evaluating the potential and problems of three-dimensional computed tomography measurements of arterial stenosis.

Volume visualization is gaining widespread acceptance in medical applications. As its use increases, the issue of accuracy becomes critical. There have been very few studies examining the accuracy of volume rendering techniques. We studied the accuracy of hardware-assisted volume rendering for measurement of arterial stenosis in computed tomography (CT) data. The results of our study reveal that accurate measurements can be made from volume rendered CT data. However, error is present (absolute average error from 5.1% to 13.6%) and there is some variability, even for experts (standard deviation ranged from 4.8% to 15%). The evidence suggests that the choice of volume rendering (transfer function) parameters greatly affects the accuracy of the results. Accurate transfer function parameter selection is a difficult problem. Parameters that produce realistic images often provide inaccurate measurements. As the use of volume visualization grows and more inexperienced users begin using these tools for medical diagnosis and staging, new guidelines, aids, and techniques must be developed to ensure reliable, accurate visualization results.