Organic data memory using the DNA approach
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: 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: 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: 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: 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: Generating Graphs for Visual Analytics through Interactive Sketching
abstract: We introduce an interactive graph generator, GreenSketch, designed to facilitate the creation of descriptive graphs required for different visual analytics tasks. The human-centric design approach of GreenSketch enables users to master the creation process without specific training or prior knowledge of graph model theory. The customized user interface encourages users to gain insight into the connection between the compact matrix representation and the topology of a graph layout when they sketch their graphs. Both the human-enforced and machine-generated randomnesses supported by GreenSketch provide the flexibility needed to address the uncertainty factor in many analytical tasks. This paper describes more than two dozen examples that cover a wide variety of graph creations from a single line of nodes to a real-life small-world network that describes a snapshot of telephone connections. While the discussion focuses mainly on the design of GreenSketch, we include a case study that applies the technology in a visual analytics environment and a usability study that evaluates the strengths and weaknesses of our design approach

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: On improving the iterative watermark embedding technique for JPEG-to-JPEG watermarking
abstract: We previously proposed an iterative technique called iterative watermark embedding (IWE) for watermark embedding in JPEG compressed domains. The proposed technique embeds the watermark successfully when the quality factor of the JPEG image is high, but when the quality factor is low, not all the bits of the watermark can be embedded. This is due to uneven distribution of capacities in different regions of the image. Moreover, the computation complexity of the iterative loop is high. In this paper we improve the technique using shuffling to equalize the capacities of different regions. Also, the iterative loop is replaced by a direct approach to reduce the computational complexity. We call this direct approach Direct JPEG Watermarking Embedding (DJWE). A Human Visual System (HVS) model is used to prioritize the DCT coefficients to achieve good visual quality. Experimental results show that the watermarks are robust against Gaussian noise attack and JPEG transcoding attacks.

title: Predictive motion estimation for reduced-resolution video from high-resolution compressed video
abstract: To convert a compressed video sequence to a lower-resolution compressed video, one typically needs to decompress the original sequence, down-sample each frame, and recompress it. It involves motion estimation in the reduced sequence which is computational intensive. We propose a novel fast algorithm to predict the motion vector of the reduced video by using the original motion information in the compressed bitstream. We achieve a much higher quality than existing algorithms with low additional complexity.

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.

title: Performance Analysis of a Pull-Based Parallel Video Server
abstract: In conventional video-on-demand systems, video data are stored in a video server for delivery to multiple receivers over a communications network. The video server's hardware limits the maximum storage capacity as well as the maximum number of video sessions that can concurrently be delivered. Clearly, these limits will eventually be exceeded by the growing need for better video quality and larger user population. This paper studies a parallel video server architecture that exploits server parallelism to achieve incremental scalability. First, unlike data partition and replication, the architecture employs data striping at the server level to achieve fine-grain load balancing across multiple servers. Second, a client-pull service model is employed to eliminate the need for interserver synchronization. Third, an admission-scheduling algorithm is proposed to further control the instantaneous load at each server so that linear scalability can be achieved. This paper analyzes the performance of the architecture by deriving bounds for server service delay, client buffer requirement, prefetch delay, and scheduling delay. These performance metrics and design tradeoffs are further evaluated using numerical examples. Our results show that the proposed parallel video server architecture can be linearly scaled up to more concurrent users simply by adding more servers and redistributing the video data among the servers.