Advanced Mid-Water Tools for 4D Marine Data Fusion and Visualization

Mapping and charting of the seafloor underwent a revolution approximately 20 years ago with the introduction of multibeam sonars -- sonars that provided complete, high-resolution coverage of the seafloor rather than sparse measurements. The initial focus of these sonar systems was the charting of depths in support of safety of navigation and offshore exploration; more recently innovations in processing software have led to approaches to characterize seafloor type and for mapping seafloor habitat in support of fisheries research. In recent years, a new generation of multibeam sonars has been developed that, for the first time, have the ability to map the water column along with the seafloor. This ability will potentially allow multibeam sonars to address a number of critical ocean problems including the direct mapping of fish and marine mammals, the location of mid-water targets and, if water column properties are appropriate, a wide range of physical oceanographic processes. This potential relies on suitable software to make use of all of the new available data. Currently, the users of these sonars have a limited view of the mid-water data in real-time and limited capacity to store it, replay it, or run further analysis. The data also needs to be integrated with other sensor assets such as bathymetry, backscatter, sub-bottom, seafloor characterizations and other assets so that a “complete” picture of the marine environment under analysis can be realized. Software tools developed for this type of data integration should support a wide range of sonars with a unified format for the wide variety of mid-water sonar types. This paper describes the evolution and result of an effort to create a software tool that meets these needs, and details case studies using the new tools in the areas of fisheries research, static target search, wreck surveys and physical oceanographic processes

GenomeFingerprinter and universal genome fingerprint analysis for systematic comparative genomics

How to compare whole genome sequences at large scale has not been achieved via conventional methods based on pair-wisely base-to-base comparison; nevertheless, no attention was paid to handle in-one-sitting a number of genomes crossing genetic category (chromosome, plasmid, and phage) with farther divergences (much less or no homologous) over large size ranges (from Kbp to Mbp). We created a new method, GenomeFingerprinter, to unambiguously produce three-dimensional coordinates from a sequence, followed by one three-dimensional plot and six two-dimensional trajectory projections to illustrate whole genome fingerprints. We further developed a set of concepts and tools and thereby established a new method, universal genome fingerprint analysis. We demonstrated their applications through case studies on over a hundred of genome sequences. Particularly, we defined the total genetic component configuration (TGCC) (i.e., chromosome, plasmid, and phage) for describing a strain as a system, and the universal genome fingerprint map (UGFM) of TGCC for differentiating a strain as a universal system, as well as the systematic comparative genomics (SCG) for comparing in-one-sitting a number of genomes crossing genetic category in diverse strains. By using UGFM, UGFM-TGCC, and UGFM-TGCC-SCG, we compared a number of genome sequences with farther divergences (chromosome, plasmid, and phage; bacterium, archaeal bacterium, and virus) over large size ranges (6Kbp~5Mbp), giving new insights into critical problematic issues in microbial genomics in the post-genomic era. This paper provided a new method for rapidly computing, geometrically visualizing, and intuitively comparing genome sequences at fingerprint level, and hence established a new method of universal genome fingerprint analysis for systematic comparative genomics.Comment: 63 pages, 15 figures, 5 table

Information visualization for mobile devices: A novel approach based on the MagicEyeView

Visualization on mobile devices not only means accommodating to a small screen space, but also widely different aspect ratios. Improving on the MagicEyeView algorithm, this paper presents a visualization technique that is better suited to screens with skewed aspects ratios. The presented approach is a focus+context visualization effort which employs distortion of coordinate scales and a "fisheye" technique. The visualization algorithm is evaluated in the problem domain of business management and the presentation of "Key Performance Indicators"