A Method for the Perceptual Optimization of Complex Visualizations

A common problem in visualization applications is the display of one surface overlying another. Unfortunately, it is extremely difficult to do this clearly and effectively. Stereoscopic viewing can help, but in order for us to be able to see both surfaces simultaneously, they must be textured, and the top surface must be made partially transparent. There is also abundant evidence that all textures are not equal in helping to reveal surface shape, but there are no general guidelines describing the best set of textures to be used in this way. What makes the problem difficult to perceptually optimize is that there are a great many variables involved. Both foreground and background textures must be specified in terms of their component colors, texture element shapes, distributions, and sizes. Also to be specified is the degree of transparency for the foreground texture components. Here we report on a novel approach to creating perceptually optimal solutions to complex visualization problems and we apply it to the overlapping surface problem as a test case. Our approach is a three-stage process. In the first stage we create a parameterized method for specifying a foreground and background pair of textures. In the second stage a genetic algorithm is applied to a population of texture pairs using subject judgments as a selection criterion. Over many trials effective texture pairs evolve. The third stage involves characterizing and generalizing the examples of effective textures. We detail this process and present some early results

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

GeoZui3D: Data Fusion for Interpreting Oceanographic Data

GeoZui3D stands for Geographic Zooming User Interface. It is a new visualization software system designed for interpreting multiple sources of 3D data. The system supports gridded terrain models, triangular meshes, curtain plots, and a number of other display objects. A novel center of workspace interaction method unifies a number of aspects of the interface. It creates a simple viewpoint control method, it helps link multiple views, and is ideal for stereoscopic viewing. GeoZui3D has a number of features to support real-time input. Through a CORBA interface external entities can influence the position and state of objects in the display. Extra windows can be attached to moving objects allowing for their position and data to be monitored. We describe the application of this system for heterogeneous data fusion, for multibeam QC and for ROV/AUV monitoring

Wetland hydrological monitoring: overview and Boxford Water Meadows case study

The aim of this report is to provide the reader with the information required to make informed decisions about the best and most appropriate way to monitor a wetland site. To achieve this aim, the report has the following objectives: 1. To outline the need and purpose for monitoring. 2. To summarise the methods used to identify and categorise wetland types. 3. To describe the broad types of monitoring that may be undertaken. 4. To give detailed information about the range of wetland monitoring techniques available. 5. To provide guidance on how to select the most appropriate monitoring techniques. 6. To illustrate, using the Boxford wetland as a case study, how the techniques described in this report can be applied, and what challenges and solutions are encountered

Relative Expression Levels Rather Than Specific Activity Plays the Major Role in Determining In Vivo AKT Isoform Substrate Specificity

The AKT protooncogene mediates many cellular processes involved in normal development and disease states such as cancer. The three structurally similar isoforms: AKT1, AKT2, and AKT3 exhibit both functional redundancy and isoform-specific functions; however the basis for their differential signalling remains unclear. Here we show that in vitro, purified AKT3 is ∼47-fold more active than AKT1 at phosphorylating peptide and protein substrates. Despite these marked variations in specific activity between the individual isoforms, a comprehensive analysis of phosphorylation of validated AKT substrates indicated only subtle differences in signalling via individual isoforms in vivo. Therefore, we hypothesise, at least in this model system, that relative tissue/cellular abundance, rather than specific activity, plays the dominant role in determining AKT substrate specificity in situ

Bioclimatic envelope model of climate change impacts on blanket peatland distribution in Great Britain

Copyright © 2010 Inter-Research.Publisher's version of record available via: doi: 10.3354/cr00911Blanket peatlands are rain-fed mires that cover the landscape almost regardless of topography. The geographical extent of this type of peatland is highly sensitive to climate. We applied a global process-based bioclimatic envelope model, PeatStash, to predict the distribution of British blanket peatlands. The model captures the present areal extent (Kappa = 0.77) and is highly sensitive to both temperature and precipitation changes. When the model is run using the UKCIP02 climate projections for the time periods 2011-2040, 2041-2070 and 2071-2100, the geographical distribution of blanket peatlands gradually retreats towards the north and the west. In the UKCIP02 high emissions scenario for 2071-2100, the blanket peatland bioclimatic space is ∼84% smaller than contemporary conditions (1961-1990); only parts of the west of Scotland remain inside this space. Increasing summer temperature is the main driver of the projected changes in areal extent. Simulations using 7 climate model outputs resulted in generally similar patterns of declining aereal extent of the bioclimatic space, although differing in degree. The results presented in this study should be viewed as a first step towards understanding the trends likely to affect the blanket peatland distribution in Great Britain. The eventual fate of existing blanket peatlands left outside their bioclimatic space remains uncertain. © Inter-Research 2010 .Environment AgencyNatural Environment Research Council (NERC)Royal Societ