Load Characterization for Distributed Virtual Environments

Due to their sensitivity to user positions, actions, and visibility, Distributed Virtual Environments (DVEs) are well served through a focused load characterization effort. Quantified load can then be evaluated through models of the system behavior, resulting in expected behavior. A discussion of determining some characterized load from system requirements and instrumenting a DVE to provide validation metrics is also provided

Interactive Visual Analysis of Structure-borne Noise Data

Numerical simulation has become omnipresent in the automotive domain, posing new challenges such as high-dimensional parameter spaces and large as well as incomplete and multi-faceted data. In this design study, we show how interactive visual exploration and analysis of high-dimensional, spectral data from noise simulation can facilitate design improvements in the context of conflicting criteria. Here, we focus on structure-borne noise, i.e., noise from vibrating mechanical parts. Detecting problematic noise sources early in the design and production process is essential for reducing a product's development costs and its time to market. In a close collaboration of visualization and automotive engineering, we designed a new, interactive approach to quickly identify and analyze critical noise sources, also contributing to an improved understanding of the analyzed system. Several carefully designed, interactive linked views enable the exploration of noises, vibrations, and harshness at multiple levels of detail, both in the frequency and spatial domain. This enables swift and smooth changes of perspective; selections in the frequency domain are immediately reflected in the spatial domain, and vice versa. Noise sources are quickly identified and shown in the context of their neighborhood, both in the frequency and spatial domain. We propose a novel drill-down view, especially tailored to noise data analysis. Split boxplots and synchronized 3D geometry views support comparison tasks. With this solution, engineers iterate over design optimizations much faster, while maintaining a good overview at each iteration. We evaluated the new approach in the automotive industry, studying noise simulation data for an internal combustion engine.acceptedVersio

Innovations in Systems and Software Engineering manuscript No. (will be inserted by the editor)

approaches and techniques for static and dynamic graphical representations of algorithms, programs (code) and the processed data. SV is concerned primarily with analysis of programs and their development. The goal is to improve our understanding of inherently invisible and intangible software, particularly when dealing with large information spaces that characterize domains like software maintenance, reverse engineering, and collaborative development. The main challenge is to find effective mappings from different software aspects to graphical representations using visual metaphors. This paper provides an overview of the SV research, describes current research directions and includes an extensive list of recommended readings.

Clarifying the complexity of emotion in HRD: The use of visualisation technology

The essence of chaos and complexity theories is that ‘simple processes in nature [can] produce magnificent edifices of complexity without randomness. In nonlinearity and feedback lay all the necessary tools for encoding and then unfolding structures as rich as the human brain’ (Gleick, 1987, p. 306-307). Faith in the tools we use, whether they are accurate or not, has brought extraordinary insights and results. For example, Weick (1995) relates the story of the soldiers who used a map of the Pyrenees to find their way successfully in the Swiss Alps. For centuries we used Newtonian laws to solve quite adequately complex problems in the physical world until the general theory of relativity provided a better understanding of what occurs in time and space. Our attempts to find tools that will better clarify the complexity that confronts us may not give us an accurate picture of ‘reality’. Nevertheless, our attempts very often yield tools that reveal extraordinary insights that are ‘real’ for those seeking answers to practical issues. Thus, in the spirit of chaos and complexity, this chapter offers a tool that represents our attempt to begin unfolding the ‘objective correlatives’ of emotion structures in the workplace that influence the practice of HRD