Discovering Knowledge Through Visual Analysis
This paper describes a vision for the near future in digital content analysis as it relates to the creation, verification, and presentation of knowledge. This paper focuses on how visualization enables humans to gain knowledge. Visualization, in this context, is not just the picture representing the data, but a two-way interaction between the human and their information resources for the purposes of knowledge discovery, verification, and the sharing of knowledge with others. We present PNNL-developed software to demonstrate how current technology can use visualization tools to analyze large diverse collections of text. This will be followed by lessons learned and the presentation of a core concept for a new human information discourse.

title: Graph Signatures for Visual Analytics
abstract: We present a visual analytics technique to explore graphs using the concept of a data signature. A data signature, in our context, is a multidimensional vector that captures the local topology information surrounding each graph node. Signature vectors extracted from a graph are projected onto a low-dimensional scatterplot through the use of scaling. The resultant scatterplot, which reflects the similarities of the vectors, allows analysts to examine the graph structures and their corresponding real-life interpretations through repeated use of brushing and linking between the two visualizations. The interpretation of the graph structures is based on the outcomes of multiple participatory analysis sessions with intelligence analysts conducted by the authors at the Pacific Northwest National Laboratory. The paper first uses three public domain data sets with either well-known or obvious features to explain the rationale of our design and illustrate its results. More advanced examples are then used in a customized usability study to evaluate the effectiveness and efficiency of our approach. The study results reveal not only the limitations and weaknesses of the traditional approach based solely on graph visualization, but also the advantages and strengths of our signature-guided approach presented in the paper

title: Organic data memory using the DNA approach
abstract: For very long-term storage and retrieval, encode information as artificial DNA strands and insert into living hosts. As vectors, bacteria, even some bugs and weeds, might be good for hundreds of millions of years.

title: Multivariate Visualization with Data Fusion
abstract: We discuss a fusion-based visualization method to analyze a multivariate climate dataset and its metadata. The primary difference between a conventional visualization and a fusion-based visualization is that the former draws on a single image whereas the latter draws on multiple see-through layers, which are then overlaid on each other to form the final visualization. We propose optimized colormaps to highlight subtle features that would not be shown with conventional colormaps. We present fusion techniques that integrate multiple single-purpose visualization techniques into the same viewing space. Our highly flexible fusion approach allows scientists to explore multiple parameters concurrently by mixing and matching images without frequently reconstructing new visualizations from the data for every possible combination. Although our primary visualization application is climate modeling, we show with examples that our fundamental design - fusing layers of data images for multivariate visualization - can be generalized for other information visualization applications.

title: Data Signatures and Visualization of Scientific Data Sets
abstract: Today, as data sets used in computations grow in size and complexity, the technologies developed over the years to deal with scientific data sets have become less efficient and effective. Many frequently used operations, such as eigenvector computation, could quickly exhaust our desktop workstations once the data size reaches certain limits. On the other hand, the high-dimensional data sets we collect every day don't relieve the problem. Many conventional metric designs that build on quantitative or categorical data sets cannot be applied directly to heterogeneous data sets with multiple data types. While building new machines with more resources might conquer the data size problems, the complexity of today's computations requires a new breed of projection techniques to support analysis of the data and verification of the results. We introduce the concept of a data signature, which captures the essence of a scientific data set in a compact format, and use it to conduct analysis as if using the original. A time-dependent climate simulation data set demonstrates our approach and presents the results.

title: Vector fields simplification-a case study of visualizing climate modeling and simulation data sets
abstract: In our study of regional climate modeling and simulation, we frequently encounter vector fields that are crowded with large numbers of critical points. A critical point in a flow is where the vector field vanishes. While these critical points accurately reflect the topology of the vector fields, in our study only a subset of them is worth further investigation. We present a filtering technique based on the vorticity of the vector fields to eliminate the less interesting and sometimes sporadic critical points in a multiresolution fashion. The neighboring regions of the preserved features, which are characterized by strong shear and circulation, are potential locations of weather instability. We apply our feature filtering technique to a regional climate modeling data set covering East Asia in the summer of 1991.

title: Novel blind multiple watermarking technique for images
abstract: Three novel blind watermarking techniques are proposed to embed watermarks into digital images for different purposes. The watermarks are designed to be decoded or detected without the original images. The first one, called single watermark embedding (SWE), is used to embed a watermark bit sequence into digital images using two secret keys. The second technique, called multiple watermark embedding (MWE), extends SWE to embed multiple watermarks simultaneously in the same watermark space while minimizing the watermark (distortion) energy. The third technique, called iterative watermark embedding (IWE), embeds watermarks into JPEG-compressed images. The iterative approach of IWE can prevent the potential removal of a watermark in the JPEG recompression process. Experimental results show that embedded watermarks using the proposed techniques can give good image quality and are robust in varying degree to JPEG compression, low-pass filtering, noise contamination, and print-and-scan.

title: Fast integer motion estimation for H.264 video coding standard
abstract: Multiple block size motion estimation is adopted in the latest JVT/H.264 video coding standard to achieve higher coding efficiency. However, full exhaustive search of all block sizes is computational intensive with motion estimation complexity increasing linearly with the number of block sizes allowed. We propose a fast integer motion estimation method for multiple block size motion estimation (FMBME) which reduces computation significantly. Experimental result shows that, compared with full search, the proposed method can have a speed up factor of four with bit-rate increases within 1%.

title: ICT production and diffusion in Asia Digital dividends or digital divide?
abstract: This paper examines the empirical evidence to determine whether Asian countries, despite having captured a disproportionately high share of global production of ICT goods, have as a group been laggard in the adoption of ICT in comparison to non-Asian countries. Using regression analysis, it is shown that as a group Asian countries have indeed had generally lower rates of ICT adoption relative to their levels of potential as predicted on the basis of their current level of development (GDP/capita) and competitiveness (world competitiveness index). In addition, disparities in ICT diffusion are found to be significantly higher among Asian countries than among non-Asian countries. In particular, a significant ‘digital divide’ is found to exist between the five more advanced countries of the region (Japan and the four Asian NIEs) and the other seven developing Asian countries. Policy implications of the findings for the Asian countries are highlighted.

title: Phylogenetic Web Profiler
abstract: Phylogenetic Web Profiler (PWP) is a web-based service designed to perform phylogenetic profiling of proteins against genomes. The current version offers a selection of 63 completed genomes and available plasmids as annotated in the PEDANT genome database. Unlike currently available applications, this tool offers several choices of ortholog prediction parameters including E-value cutoff, percent length difference tolerance, and annotation similarity. Additional features include tight integration with the PEDANT database and tools to analyze properties of predicted proteins. PWP should prove very useful for the analysis of functional-linkage between proteins.

title: Rate estimation for H.264/AVC spatial resolution reduction
abstract: The emergence of wireless networks has posed new challenges for multimedia content providers. In particular, many existing video contents have bit-rates and resolutions far exceeding the capability of wireless networks and mobile devices and they need to be adapted before transmission. In this paper, we propose a technique using /spl rho/-domain information to estimate the bit rate of down-sampled video in the H.264/AVC format. The bit rate is estimated in two stages. In the initialization stage, we use a low-complexity algorithm to estimate the /spl rho/-domain parameters for half and quarter resolutions, respectively. In the refinement stage, the estimation error is feed-forwarded to improve the estimation accuracy. Experimental results show that the proposed technique can estimate the bit rate accurately at a wide range of down-sampling ratios.