Visual support for the understanding of simulation processes

Current visualization systems are typically based on the concept of interactive post-processing. This decoupling of data visualiza-tion from the process of data generation offers a flexible applica-tion of visualization tools. It can also lead, however, to information loss in the visualization. Therefore, a combination of the visual-ization of the data generating process with the visualization of the produced data offers significant support for the understanding of the abstract data sets as well as the underlying process. Due to the application-specific characteristics of data generating processes, the task requires tailored visualization concepts. In this work, we focus on the application field of simulating biochemical reaction networks as discrete-event systems. These stochastic processes generate multi-run and multivariate time-series, which are analyzed and compared on three different process levels: model, experiment, and the level of multi-run simulation data, each associated with a broad range of analysis goals. To meet these challenging characteristics, we present visualization concepts specifically tailored to all three process levels. The fundament of all three visualization concepts is a compact view that relates the multi-run simulation data to the characteristics of the model structure and the experiment. The view provides the visualization at the experi-ment level. The visualization at the model level coordinates mul-tiple instances of this view for the comparison of experiments. At the level of multi-run simulation data, the views gives an overview on the data, which can be analyzed in detail in time-series views suited for the analysis goals. Although we derive our visualization concepts for one concrete simulation process, our general concept of tailoring the visualization concepts to process levels is generally applicable for the visualization of simulation processes

Visual Support for the Modeling and Simulation of Cell Biological Processes

This dissertation aims at bringing information visualization closer to the demands of analytical problem solving for the specific domain of modeling and simulating cell biological systems. To this end, main segments of visual support in the domain are identified. For one of these segments, the visual analysis of simulation data, new concepts are developed. First, this includes the visualization of simulation data in the context of data generation. Second, new multiple view techniques for large and complex simulation data are introduced.Diese Arbeit verfolgt das Ziel, Informationsvisualisierung näher an die Anforderungen des Analyseprozesses heranzuführen, mit Blick auf die konkrete Anwendung der Modellierung und Simulation zellbiologischer Systeme. Dazu werden wesentliche Teilbereiche der visuellen Unterstützung identifiziert. Für den Teilbereich der visuellen Analyse von Simulationsdaten werden neue Konzepte entwickelt. Dies beinhaltet zum einen die Visualisierung von Simulationsdaten im Kontext der Datengenerierung. Zum anderen werden neue Multiple-View-Techniken für große und komplexe Simulationsdaten vorgestellt

Objective and subjective aspects of an urban square’s human comfort – case study in Szeged (Hungary)

This paper deals with the first comprehensive thermal comfort study made in the centre of Szeged, a southern Hungarian town. We calculated the Predicted Mean Vote index with the RayMan model from measured meteorological parameters (objective approach). Within the frameworks of a simultaneously conducted social survey people estimated their thermal comfort (Actual Sensation Vote), so we could compare these subjective values with the objective results. We recorded also a number of subjective features on questionnaires in order to determine which factors influence the thermal comfort the most

A visual analytics tool to validate simulation models against collected data. V. 1.0.0

The validation of a simulation model is a crucial task in model development. It involves the comparison of simulation data to observation data and the identification of suitable model parameters. SLIVISU is a Visual Analytics framework that enables geoscientists to perform these tasks for observation data that is sparse and uncertain. Primarily, SLIVISU was designed to evaluate sea level indicators, which are geological or archaeological samples supporting the reconstruction of former sea level over the last ten thousands of years and are compiled in a postgreSQL database system. At the same time, the software aims at supporting the validation of numerical sea-level reconstructions against this data by means of visual analytics

Dispensing pico to nanolitre of a natural hydrogel by laser-assisted bioprinting

<p>Abstract</p> <p>Background</p> <p>Laser-assisted bioprinting of multi-cellular replicates in accordance with CAD blueprint may substantially improve our understandings of fundamental aspects of 3 D cell-cell and cell-matrix interactions <it>in vitro</it>. For predictable printing results, a profound knowledge about effects of different processing parameters is essential for realisation of 3 D cell models with well-defined cell densities.</p> <p>Methods</p> <p>Time-resolved imaging of the hydrogel jet dynamics and quantitative assessment of the dependence of printed droplet diameter on the process characteristics were conducted.</p> <p>Results</p> <p>The existence of a counterjet was visualised, proving the bubble collapsing theory for the jet formation. Furthermore, by adjusting the viscosity and height of the applied hydrogel layer in combination with different laser pulse energies, the printing of volumes in the range of 10 to 7000 picolitres was demonstrated. Additionally, the relationship between the viscosity and the layer thickness at different laser pulse energies on the printed droplet volume was identified.</p> <p>Conclusions</p> <p>These findings are essential for the advancement of laser-assisted bioprinting by enabling predictable printing results and the integration of computational methods in the generation of 3 D multi-cellular constructs.</p