13 Zentrale Universitätseinrichtungen

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/14

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Open Access
Mapping molecular surfaces of arbitrary genus to a sphere
(2015) Frieß, Florian
Molecular surfaces are one of the most widely used visual representations for the analysis of molecules. They allow different properties of the molecule to be shown and allow additional information to be added, such as chemical properties of the atoms, using colour. With the usual representation of molecular surfaces being three dimensional there are common problems, such as occlusion and view-dependency. To solve these problems a two dimensional representation of the molecular surface can be created. For molecules with a surface of genus zero there are different methods of creating the sphere that is used as an intermediate object to create the map. For molecules with a higher genus this process becomes more difficult. Tunnels can only be mapped to the sphere if they are closed at some point inside the tunnel. Introducing arbitrary cuts can lead to small areas on the map. The deeper inside the tunnel the cut is placed the smaller the area. To avoid these small areas the cuts have to be placed close to the entrance of the tunnel. Therefore a mesh segmentation is performed to identify the tunnel and to create a genus zero surface for the molecule. Based on this identification further information can be displayed, such as geodesic lines showing how the tunnels are connected.
Open Access
Code execution reports: visually augmented summaries of executed source code fragments
(2016) Siddiqui, Hafiz Ammar
Understanding a fragment of code is important for developers as it enables them to optimize, debug and extend it. Developers adopt different procedures for understanding a piece of code, which involves going through the source code, documentation, and profilers results. Various code comprehension techniques have suggested code summarization approaches, which generates the intended behavior of code in natural language text. In this thesis, we present an approach to summarize the actual behavior of a method during its execution. For this purpose, we create a framework that facilitates the generation of interactive and web-based natural language reports with small embedded word-size visualizations. Then, we develop a tool that profiles a method for runtime behavior, and then it processes the information. The tool uses our framework to generate a visually augmented natural language summary report that explains the behavior of the code. In the end, we conduct a small user study to evaluate the quality of our code execution reports.
Open Access
3D visualization of multivariate data
(2012) Sanftmann, Harald; Weiskopf, Daniel (Prof. Dr.)
Nowadays large amounts of data are organized in tables, especially in relational databases where the rows store the data items to which multiple attributes are stored in the columns. Information stored this way, having multiple (more than two or three) attributes, can be treated as multivariate data. Therefore, visualization methods for multivariate data have a large application area and high potential utility. This thesis focuses on the application of 3D scatter plots for the visualization of multivariate data. When dealing with 3D, spatial perception needs to be exploited, by effectively using depth cues to convey spatial information to the user. To improve the presentation of individual 3D scatter plots, a technique is presented that applies illumination to them, thus using the shape-from-shading depth cue. To enable the analysis not only of 3D but of multivariate data, a novel technique is introduced that allows the navigation between 3D scatter plots. Inspecting the large number of 3D scatter plots that can be projected from a multivariate data set is very time consuming. The analysis of multivariate data can benefit from automatic machine learning approaches. A presented method uses decision trees to increase the speed a user can gain an understanding of the multivariate data at no extra cost. Stereopsis can also support the display of 3D scatter plots. Here an improved anaglyph rendering technique is presented, significantly reducing ghosting artifacts. The technique is not only applicable for information visualization, but for general rendering or to present stereoscopic image data. Some information visualization algorithms require high computation time. Many of these algorithms can be parallelized to run interactively. A framework that supports the parallelization on shared and distributed memory systems is presented.
Open Access
Visual analytics of big data from distributed systems
(2017) Kutzleb, André
Distributed Systems are challenging to debug because the temporal order of events and distributed states are hard to track. The high complexity of distributed systems make fully automatic reasoning difficult to apply. Domain experts are often required to reason about the behavior of a system based on log files from various sources. This situation presents a good opportunity for visual analytics. Data from multiple sources can be preprocessed and visualized, and then domain experts can conduct exploratory analysis to accelerate the identification of issues. The goal of this master thesis was to create such a visual analytics tool to help domain experts explore data collected from distributed systems more efficiently and assist in identifying bugs and anomalies. The system was used by domain experts and helped to identify issues in a distributed system, showing that visual analytics can be a useful tool to assist domain experts in their daily work.
Open Access
Visualizing Optimization Trajectories
(2019) Hägele, David
Nonlinear constraint optimization has many applications in technical, scientific as well as economic fields. Understanding solver behavior can help to improve solvers, choose appropriate hyperparameters, and formulate better performing nonlinear programs. This thesis proposes a visual analytics tool for analyzing constraint optimization problems. The optimization process is depicted by a set of two-dimensional trajectories, representing the trace of intermediate solutions during the optimization process. This allows us to obtain an overview of the evolution of the optimization process. To support detailed analysis, supplemental views are added to show the constraints violations and areas of feasible solution. Furthermore, different interaction techniques are implemented to facilitate the exploration process. To showcase the usefulness of the approach, findings from an exemplary analysis based on optimization logs of robot motion planning are presented.
Open Access
Online visualization of German power plants and their production
(2017) Ullah, Kazi Riaz
Maps are used for centuries to visualize geographical or topological information and nowadays, with modern technology, we can create interactive maps that allow us to display and access additional information. Some of them have even become part of our daily life, such as, almost real-time traffic information. Furthermore, maps are often used to display data of population densities, temperatures and spatial distribution of geographical phenomenon. Fraunhofer Institute of Solar Energy ISE decided to build an interactive map that shows the locations of all power plants listed on the European Energy Exchange (EEX). Since July 2014, the Fraunhofer ISE has been providing interactive charts on electricity production and other related information about electricity and power generation in Germany. These charts became very popular and widely used by people from different professions, namely scientists, politicians, journalists as well as online/printed media. Due to the high popularity of these interactive energy charts, an interactive map has been added to the Energy Charts data visualization portal to make the framework more informative and interesting for users. The map has several search options and levels of detail for searching different power plant locations, technical data, and connectivity to the high voltage transmission lines. Furthermore, this new visualization framework is interconnected with the existing energy charts. The dynamic linking, brushing and filtering technique in both map and energy charts have enhanced the framework by an additional layer providing more visibility and information on the selected power plants.
Open Access
Visualization and mesoscopic simulation in systems biology
(2013) Falk, Martin Samuel; Ertl, Thomas (Prof. Dr.)
A better understanding of the internal mechanisms and interplays within a single cell is key to the understanding of life. The focus of this thesis lies on the mechanism of cellular signal transduction, i.e. relaying a signal from outside the cell by different means of transport toward its target inside the cell. Besides experiments, understanding can also be achieved by numerical simulations of cellular behavior which require theoretical models to be designed and evaluated. This is where systems biology closely relates and depends on recent research results in computer science in order to deal with the modeling, the simulation, and the analysis of the computational results. Since a single cell can consist of billions of atoms, the simulation of intracellular processes requires a simplified, mesoscopic model. The simulation domain has to be three dimensional to consider the spatial, possibly asymmetric, intracellular architecture filled with individual particles representing signaling molecules. In contrast to continuous models defined by systems of partial differential equations, a particle-based model allows tracking individual molecules moving through the cell. The overall process of signal propagation usually requires between minutes and hours to complete, but the movement of molecules and the interactions between them have to be determined in the microsecond range. Hence, the computation of thousands of consecutive time steps is necessary, requiring several hours or even days of computational time for a non-parallel simulation. To speed up the simulation, the parallel hardware of current central processing units (CPUs) and graphics processing units (GPUs) can be employed. Finally, the resulting data has to be analyzed by domain experts and, therefore, has to be represented in meaningful ways. Typical prevalent analysis methods include the aggregation of the data in tables or simple 2D graph plots, sometimes 3D plots for continuous data. Despite the fact that techniques for interactive visualization of data in 3D are well-known, so far none of the methods have been applied to the biological context of single cell models and specialized visualizations fitted to the experts’ need are missing. Another issue is the hardware available to the domain experts that can be used for the task of visualizing the increasing amount of time-dependent data resulting from simulations. It is important that the visualization keeps up with the simulations to ensure that domain experts can still analyze their data sets. To deal with the massive amount of data to come, compute clusters will be necessary with specialized hardware dedicated to data visualization. It is, thus, important, to develop visualization algorithms for this dedicated hardware, which is currently available as GPU. In this thesis, the computational power of recent many-core architectures (CPUs and GPUs) is harnessed for both the simulation and the visualizations. Novel parallel algorithms are introduced to parallelize the spatio-temporal, mesoscopic particle simulation to fit the architectures of CPU and GPU in a similar way. Besides molecular diffusion, the simulation considers extracellular effects on the signal propagation as well as the import of molecules into the nucleus and a dynamic cytoskeleton. An extensive comparison between different configurations is performed leading to the conclusion that the usage of GPUs is not always beneficial. For the visual data analysis, novel interactive visualization techniques were developed to visualize the 3D simulation results. Existing glyph-based approaches are combined in a new way facilitating the visualization of the individual molecules in the interior of the cell as well as their trajectories. A novel implementation of the depth of field effect combined with additional depth cues and coloring aid the visual perception and reduce visual clutter. To obtain a continuous signal distribution from the discrete particles, techniques known from volume rendering are employed. The visualization of the underlying atomic structures provides new detailed insights and can be used for educational purposes besides showing the original data. A microscope-like visualization allows for the first time to generate images of synthetic data similar to images obtained in wet lab experiments. The simulation and the visualizations are merged into a prototypical framework, thereby supporting the domain expert during the different stages of model development, i.e. design, parallel simulation, and analysis. Although the proposed methods for both simulation and visualization were developed with the study of single-cell signal transduction processes in mind, they are also applicable to models consisting of several cells and other particle-based scenarios. Examples in this thesis include the diffusion of drugs into a tumor, the detection of protein cavities, and molecular dynamics data from laser ablation simulations, among others.
Open Access
Advanced visualization techniques for flow simulations : from higher-order polynomial data to time-dependent topology
(2013) Üffinger, Markus; Ertl, Thomas (Prof. Dr.)
Computational Wuid dynamics (CFD) has become an important tool for predicting Fluid behavior in research and industry. Today, in the era of tera- and petascale computing, the complexity and the size of simulations have reached a state where an extremely large amount of data is generated that has to be stored and analyzed. An indispensable instrument for such analysis is provided by computational Wow visualization. It helps in gaining insight and understanding of the Wow and its underlying physics, which are subject to a complex spectrum of characteristic behavior, ranging from laminar to turbulent or even chaotic characteristics, all of these taking place on a wide range of length and time scales. The simulation side tries to address and control this vast complexity by developing new sophisticated models and adaptive discretization schemes, resulting in new types of data. Examples of such emerging simulations are generalized Vnite element methods or hp-adaptive discontinuous Galerkin schemes of high-order. This work addresses the direct visualization of the resulting higher-order Veld data, avoiding the traditional resampling approach to enable a more accurate visual analysis. The second major contribution of this thesis deals with the inherent complexity of Wuid dynamics. New feature-based and topology-based visualization algorithms for unsteady Wow are proposed to reduce the vast amounts of raw data to their essential structure. For the direct visualization pixel-accurate techniques are presented for 2D Veld data from generalized Vnite element simulations, which consist of a piecewise polynomial part of high order enriched with problem-dependent ansatz functions. Secondly, a direct volume rendering system for hp-adaptive Vnite elements, which combine an adaptive grid discretization with piecewise polynomial higher-order approximations, is presented. The parallel GPU implementation runs on single workstations, as well as on clusters, enabling a real-time generation of high quality images, and interactive exploration of the volumetric polynomial solution. Methods for visual debugging of these complex simulations are also important and presented. Direct Wow visualization is complemented by new feature and topology-based methods. A promising approach for analyzing the structure of time-dependent vector Velds is provided by Vnite-time Lyapunov exponent (FTLE) Velds. In this work, interactive methods are presented that help in understanding the cause of FTLE structures, and novel approaches to FTLE computation are developed to account for the linearization error made by traditional methods. Building on this, it is investigated under which circumstances FTLE ridges represent Lagrangian coherent structures (LCS)—the timedependent counterpart to separatrices of traditional “steady” vector Veld topology. As a major result, a novel time-dependent 3D vector Veld topology concept based on streak surfaces is proposed. Streak LCS oUer a higher quality than corresponding FTLE ridges, and animations of streak LCS can be computed at comparably low cost, alleviating the topological analysis of complex time-dependent Velds.
Open Access
Visualization techniques for parallel coordinates
(2013) Heinrich, Julian; Weiskopf, Daniel (Prof. Dr.)
Visualization plays a key role in knowledge discovery, visual data exploration, and visual analytics. Static images are an effective tool for visual communication, summarization, and pattern extraction in large and complex datasets. Only together with human-computer-interaction techniques, visual interfaces enable an analyst to explore large information spaces and to drive the whole analytical reasoning process. Scatterplots and parallel coordinates are well-recognized visualization techniques that are commonly employed for statistics (both explorative and descriptive) and data-mining, but are also gaining importance for scientific visualization. While scatterplots are restricted to the display of at most three dimensions due to the orthogonal layout of coordinate axes, a parallel arrangement allows for the visualization of multiple attributes of a dataset. Although both techniques rely on projections of higher-dimensional geometry and are related by a point–line duality, parallel coordinates enjoy great popularity for the visualization and analysis of multivariate data. Despite their popularity, parallel coordinates are subject to a number of limitations that remain to be solved. For large datasets, the potentially high amount of overlapping lines may hinder the observer from visually extracting meaningful patterns. Encoding observations with polylines make it difficult to follow lines over all dimensions, as they lose visual continuation across the axes. Clusters cannot be represented by the geometry of lines, and the order of axes has a high impact on the patterns exhibited by parallel coordinates. This thesis presents visualization techniques for parallel coordinates that address these limitations. As a foundation, an extensive review of the state of the art of parallel coordinates will be given. Based on the point–line duality, the existing model of continuous scatterplots is adapted to parallel coordinates for the visualization of data defined on continuous domains. To speed up computation and obtain interactive frame rates, a scalable and progressive rendering algorithm is introduced that further allows for arbitrary reconstruction and interpolation schemes. A curve-bundling model for parallel coordinates is evaluated with a user study showing that bundling is effective for cluster visualization based on geometric cues while being equally capable of revealing correlations between neighboring axes. To address the axis-order problem, a graph-based approach is presented that allows for the visualization of all pairwise relations in a matrix layout without redundancy. Finally, the use of parallel coordinates is demonstrated for real datasets from computational fluid dynamics, motion capturing, bioinformatics, and systems biology.
Open Access
Visual Parameter Space Analysis for Classification Models
(2019) Heyen, Frank
We present a batch training and visualization system that enables users to visually compare different classifiers and parameter configurations in their performance and behavior. Our approach is plugin-based and classifier-agnostic and allows users to add their own datasets and classifier implementations. It provides multiple visualizations, including a multivariate ranking, a similarity map, a scatterplot that shows correlations between parameters and scores, as well as a training history chart. We enable users to interactively filter, highlight, colorize, sort, and group the displayed data. Using an iterative process, we developed our approach over the course of six months in cooperation with domain experts who apply machine learning for natural language processing. Our evaluation consists of two pair analytics studies and a survey with students. It demonstrates the effectiveness and usability of the implementation and shows desire to use it from domain experts, teachers and students.

13 Zentrale Universitätseinrichtungen

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