Visual Analysis of Overlapping Biological Networks
This paper investigates a new problem of visualizing a set of overlapping networks. We present two methods for constructing visualization of two and three overlapping networks in three dimensions. Our methods aim to achieve both drawing aesthetics (or conventions) for each individual network and exposing the common nodes between the overlapping networks. We evaluated our approaches using biological networks including protein interaction network, metabolic network, and gene regulatory network, from the bacterium Escherichia coli and crop plants to demonstrate their usefulness to support biological analysis.

title: Gene Specific Co-regulation Discovery: An Improved Approach
abstract: Discovering gene co-regulatory relationships is a new but important research problem in DNA microarray data analysis. The problem of gene specific co-regulation discovery is to, for a particular gene of interest, called the target gene , identify its strongly co-regulated genes and the condition subsets where such strong gene co-regulations are observed. The study on this problem can contribute to a better understanding and characterization of the target gene. The existing method, using the genetic algorithm (GA), is slow due to its expensive fitness evaluation and long individual representation. In this paper, we propose an improved method for finding gene specific co-regulations. Compared with the current method, our method features a notably improved efficiency. We employ k NN Search Table to substantially speed up fitness evaluation in the GA. We also propose a more compact representation scheme for encoding individuals in the GA, which contributes to faster crossover and mutation operations. Experimental results with a real-life gene microarray data set demonstrate the improved efficiency of our technique compared with the current method.

title: Workshop Organizers' Message
abstract: International Workshop on Privacy-Preserving Data Analysis (PPDA) 2009 took place at Brisbane, Australia on 21st April, 2009. There were two sessions for this workshop with 2 paper presentations in the first session and 3 presentations in the second session. 
 
With the advancement of information technology and declining hardware price, organizations and companies are able to collect large amount of personal data. Moreover, advanced data analysis and mining techniques have been proposed to derived patterns hidden in data. However, the increasing power in data processing and analysis also raises concerns over the proper usage of personal information. Without proper treatment of the threat of sensitive information leakage, organizations would be reluctant to disclose their data even when there may be great potential gains from the data exploration. Therefore research in the area of privacy preservation is deemed important for both theoretical and practical reasons. PPDA 2009 was held in conjunction with DASFAA 2009 conference, and aims to bring together researchers in different fields related to privacy preserving data analysis and to provide a forum where researchers and practitioners can share and exchange their knowledge and experiences.

title: A Multiresolution Terrain Model for Efficient Visualization Query Processing
abstract: Multiresolution triangular mesh (MTM) models are widely used to improve the performance of large terrain visualization by replacing the original model with a simplified one. MTM models, which consist of both original and simplified data, are commonly stored in spatial database systems due to their size. The relatively slow access speed of disks makes data retrieval the bottleneck of such terrain visualization systems. Existing spatial access methods proposed to address this problem rely on main-memory MTM models, which leads to significant overhead during query processing. In this paper, we approach the problem from a new perspective and propose a novel MTM called direct mesh that is designed specifically for secondary storage. It supports available indexing methods natively and requires no modification to MTM structure. Experiment results, which are based on two real-world data sets, show an average performance improvement of 5-10 times over the existing methods

title: A multi-resolution surface distance model for k-NN query processing
abstract: A spatial k-NN query returns k nearest points in a point dataset to a given query point. To measure the distance between two points, most of the literature focuses on the Euclidean distance or the network distance. For many applications, such as wildlife movement, it is necessary to consider the surface distance, which is computed from the shortest path along a terrain surface. In this paper, we investigate the problem of efficient surface k-NN (sk-NN) query processing. This is an important yet highly challenging problem because the underlying environment data can be very large and the computational cost of finding the shortest path on a surface can be very high. To minimize the amount of surface data to be used and the cost of surface distance computation, a multi-resolution surface distance model is proposed in this paper to take advantage of monotonic distance changes when the distances are computed at different resolution levels. Based on this innovative model, sk-NN queries can be processed efficiently by accessing and processing surface data at a just-enough resolution level within a just-enough search region. Our extensive performance evaluations using real world datasets confirm the efficiency of our proposed model.

title: Seeing more than the graph: evaluation of multivariate graph visualization methods
abstract: Many real-world networks are multivariate, i.e., they have attributes associated with nodes and/or edges. Examples include social networks whose nodes represent people and edges represent relationships. There is usually information about each person (such as name, age, and gender) and the relationship (such type, duration, and strength). Besides common graph analysis tasks (such as identifying the most influential or structurally important nodes), there are more complex analyses for multivariate networks. One of these is the multivariate graph clustering, i.e., identifying clusters formed by nodes that have similar attributes and are close to each other in terms of graph distance. For instance, in social network analysis, it is interesting to sociologists whether or not people with similar characteristics (node attributes) are also connected to each other. Currently there are very few visualization methods available for such analysis.
 Graph and multivariate visualization have been well studied separately in the literature. Herman et al. summarized the recent work on graph visualization , and Wong and Bergeron covered the development in multivariate visualization . However, there is relatively less work available on multivariate network visualization. Two types of approaches are commonly used. The first one is the mapping approach, which maps attributes to visual elements of a node or edge. A simple example is to map one attribute to node size and another to node color . A more advanced mapping approach uses glyphs to represent node or edge attributes. One such example is to use the length and width of a rectangle node glyph to represent two node attributes . The second one is the 2.5D approach: it uses the third dimension to present the multivariate information, while the graph is shown on a 2D plane. Examples include the recently proposed "GraphScape" , which adopts a landscape metaphor: each attribute is represented by a two-and-a-half- dimensional surface, whose height indicates its value.
 Each approach has its strength and weakness. The mapping approach is effective of showing numerical value using visual element such as size, but it can be difficult to compare the value of attributes represented by different elements such as size and color. The problem is alleviated by a carefully designed glyph, but visual complexity increases quickly as the number of attributes that a glyph needs to represent grows. The 2.5D approach is good at showing the distribution of attribute values over the network, but the attribute surface could introduce occlusion and affect the visibility of underlying network.
 In this paper, we present a study evaluating the effectiveness of these two approaches for different analysis tasks. We compare the performance of mapping and 2.5D approach in a controlled lab environment. We included both simple tasks (such as identifying nodes with the largest attribute value) and complex tasks (such as multivariate graph clustering). The performance is measured both in terms of accuracy and completion time. The results indicate that statistically mapping approach performs better for the simple tasks, while the 2.5D approach is favored in the complex task. The outcomes from this study provide some guidelines for the design of effective multivariate graph visualization for different analysis tasks.

title: An Investigation of the Intrinsic Force Sensing Capabilities of Continuum Robots
abstract: This paper presents the theoretical analysis and the experimental validation of the force sensing capabilities of continuum robots. These robots employ superelastic NiTi backbones and actuation redundancy. The paper uses screw theory to analyze the limitations and provide geometric interpretation to the sensible wrenches. The analysis is based on the singular value decomposition of the Jacobian mapping between the configuration space and the twist space of the end effector. The results show that the sensible wrenches belong to a 2-D screw system and the insensible wrenches belong to a 4-D screw system. The theory presented in this paper is validated through simulations and experiments. It is shown that the force sensing errors have an average of 0.34 g with a standard deviation of 0.83 g. Another experiment of generating the stiffness map of a silicone strip suggests possible medical application of palpation for tumor detection. The presented study allows force sensing in challenging environments where placing force sensors at the distal end of a robot is not possible due to limitations such as size and MRI compatibility.

title: Design and Integration of a Telerobotic System for Minimally Invasive Surgery of the Throat
abstract: In this paper we present the clinical motivation, design specifications, kinematics, statics, and actuation compensation for a newly constructed telerobotic system for Minimally Invasive Surgery (MIS) of the throat. A hybrid dual-arm telesurgical slave, with 20 joint-space Degrees-of-Freedom (DoFs), is used in this telerobotic system to provide the necessary dexterity in deep surgical fields such as the throat. The telerobotic slave uses novel continuum robots that use multiple super-elastic backbones for actuation and structural integrity. We present the kinematics of the telesurgical slave and methods for actuation compensation to cancel the effects of backlash, friction, and flexibility of the actuation lines. A method for actuation compensation is presented in order to overcome uncertainties of modeling, friction, and backlash. This method uses a tiered hierarchy of two novel approaches of actuation compensation for remotely actuated snake-like robots. The tiered approach for actuation compensation uses compensation in both joint space and configuration space of the continuum robots. These hybrid actuation compensation schemes use intrinsic model information and external data through a recursive linear estimation algorithm and involve compensation using configuration space and joint space variables. Experimental results validate the ability of our integrated telemanipulation system through experiments of suturing and knot tying in confined spaces.

title: An adaptive octree textures painting algorithm
abstract: Traditional Texturing using a set of two dimensional image maps is an established and widespread practice. However, it is difficult to parameterize a model in texture space, particularly with representations such as implicit surfaces, subdivision surfaces, and very dense or detailed polygonal meshes. Based on an adaptive octree textures definition, this paper proposes a direct reverse-projecting pixel-level painting approach which has less storage requirements to general octree textures maps. In addition, it depends on texture lookup in the GPU, which particularly lookup faster than the non-GPU program.

title: Feature-aligned shape texturing
abstract: The essence of a 3D shape can often be well captured by its salient feature curves. In this paper, we explore the use of salient curves in synthesizing intuitive, shape-revealing textures on surfaces. Our texture synthesis is guided by two principles: matching the direction of the texture patterns to those of the salient curves, and aligning the prominent feature lines in the texture to the salient curves exactly. We have observed that textures synthesized by these principles not only fit naturally to the surface geometry, but also visually reveal, even reinforce, the shape's essential characteristics. We call these feature-aligned shape texturing. Our technique is fully automatic, and introduces two novel technical components in vector-field-guided texture synthesis: an algorithm that orients the salient curves on a surface for constrained vector field generation, and a feature-to-feature texture optimization.

title: A simple and stable feature-preserving smoothing method for contours-based reconstructed meshes
abstract: In this paper, we develop a new feature preserving smoothing method for the irregular and coarse meshes reconstructed from 2D contours. To make the feature detecting robust, a new detecting algorithm using the continuity among adjacent contours is proposed. Then the original mesh is subdivided adaptively according to the detected geometric features and smoothed with isotropic method. With the help of that, our algorithm obtains not only the feature-preserving result of anisotropic methods but also the simple and stable process of isotropic ones. After smoothing, the resolution of mesh can be resumed by moving the vertices in the original mesh to the positions of their corresponding vertices in the smoothed adaptive mesh. For smoothing of contours-based reconstructed meshes, experimental results show that our method can smooth the meshes satisfactorily and preserve their geometric features much better than other implemented methods.