Showing papers in "Journal of Visualization in 2022"

Spatiotemporal superresolution measurement based on POD and sparse regression applied to a supersonic jet measured by PIV and near-field microphone

Abstract: The present study proposed the framework of the spatiotemporal superresolution measurement based on the sparse regression with dimensionality reduction using the proper orthogonal decomposition (POD). The non-time-resolved particle image velocimetry (PIV) and the time-resolved near-field acoustic measurements using microphones were simultaneously performed for a Mach 1.35 supersonic jet. POD is applied to PIV and microphone data matrices, and the sparse linear regression model of the reduced-order data is calculated using the least absolute shrinkage and selection operator regression. The effects of the hyperparameters of the superresolution measurement were quantitatively evaluated through randomized cross-validation. The superresolved velocity field indicated the smooth convection of the velocity fluctuations associated with the screech tone, while the convection of the large-scale structures at the downstream side was not observed. The proposed framework can reconstruct the unsteady fluctuation with multiple frequency phenomena, although the reconstruction is limited to the phenomena that are associated with the microphone output.

Visual analysis of blow molding machine multivariate time series data

Abstract: The recent development in the data analytics field provides a boost in production for modern industries. Small-sized factories intend to take full advantage of the data collected by sensors used in their machinery. The ultimate goal is to minimize cost and maximize quality, resulting in an increase in profit. In collaboration with domain experts, we implemented a data visualization tool to enable decision-makers in a plastic factory to improve their production process. The tool is an interactive dashboard with multiple coordinated views supporting the exploration from both local and global perspectives. In summary, we investigate three different aspects: methods for preprocessing multivariate time series data, clustering approaches for the already refined data, and visualization techniques that aid domain experts in gaining insights into the different stages of the production process. Here we present our ongoing results grounded in a human-centered development process. We adopt a formative evaluation approach to continuously upgrade our dashboard design that eventually meets partners' requirements and follows the best practices within the field. We also conducted a case study with a domain expert to validate the potential application of the tool in the real-life context. Finally, we assessed the usability and usefulness of the tool with a two-layer summative evaluation that showed encouraging results.

Touching data with PropellerHand

Abstract: Abstract Immersive analytics often takes place in virtual environments which promise the users immersion. To fulfill this promise, sensory feedback, such as haptics, is an important component, which is however not well supported yet. Existing haptic devices are often expensive, stationary, or occupy the user’s hand, preventing them from grasping objects or using a controller. We propose PropellerHand, an ungrounded hand-mounted haptic device with two rotatable propellers, that allows exerting forces on the hand without obstructing hand use. PropellerHand is able to simulate feedback such as weight and torque by generating thrust up to 11 N in 2-DOF and a torque of 1.87 Nm in 2-DOF. Its design builds on our experience from quantitative and qualitative experiments with different form factors and parts. We evaluated our prototype through a qualitative user study in various VR scenarios that required participants to manipulate virtual objects in different ways, while changing between torques and directional forces. Results show that PropellerHand improves users’ immersion in virtual reality. Additionally, we conducted a second user study in the field of immersive visualization to investigate the potential benefits of PropellerHand there. Graphical abstract

The ThreadRadar visualization for debugging concurrent Java programs

Abstract: Abstract Due to non-deterministic behavior and thread interleaving of concurrent programs, the debugging of concurrency and performance issues is a rather difficult and often tedious task. In this paper, we present an approach that combines statistical profiling, clustering and visualization to facilitate this task. We implemented our approach in a tool which is integrated as a plugin into a widely used IDE. First, we introduce our approach with details on the profiling and clustering strategy that produce runtime metrics and clusters of threads for source-code artifacts at different levels of abstraction (class and method) and the entire program. Next, we explain the design of our visualization which represents the clusters in situ, i.e., embedded in the program text next to the related source-code artifact in the source-code editor. More detailed information is available in separate windows that also allow the user to configure thread filters interactively. In a demonstration study, we illustrate the usefulness of the tool for understanding and fixing performance and concurrency issues. Finally, we report on first formative results from a usability test and consequently implemented tool improvements. Graphical abstract

Visual variables and configuration of software maps

Abstract: Abstract Software maps provide a general-purpose interactive user interface and information display in software analytics. This paper classifies software maps as a containment-based treemap embedded into a 3D attribute space and introduces respective terminology. It provides a comprehensive overview of advanced visual metaphors and techniques, each suitable for interactive visual analytics tasks. The metaphors and techniques are briefly described, located within a visualization pipeline model, and considered within a software map design space. The general expressiveness and applicability of visual variables are detailed and discussed. Consequent applications and use cases for different software system data and software engineering data are discussed, arguing for the versatile use of software maps in visual software analytics.