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Virtuelle Umgebungen
(2000)
In this paper we present a new storytelling approach, called Hypermedia Novel (HYMN), that extends the classical narration concept of a story. We develop an underlying modular concept – the narration module – that facilitates a new manner of reception as well as creation of a story. The HYMN focuses on the recipient and his role of consuming a story and a heterogeneous group of creative authors by providing narration modules and their interfaces without defining the granularity of the modules. Using several kinds ofmultimedia elements and a hyperlink structure, we present a first demonstrator that implements this new concept. We also discuss improvements, e.g. MPEG-4/7, that support both reception by the audience, and the process of creating the story by a dispersed team of authors.
Clusters of commodity PCs are widely considered as the way to go to improve rendering performance and quality in many real-time rendering applications. We describe the design and implementation of our parallel rendering system for real-time rendering applications. Major design objectives for our system are: usage of commodity hardware for all system components, ease of integration into existing Virtual Environments software, and flexibility in applying different rendering techniques, e.g. using ray tracing to render distinct objects with a particularly high quality.
Bond graph modelling was devised by Professor Paynter at the Massachusetts Institute of Technology in 1959 and subsequently developed into a methodology for modelling multidisciplinary systems at a time when nobody was speaking of object-oriented modelling. On the other hand, so-called object-oriented modelling has become increasingly popular during the last few years. By relating the characteristics of both approaches, it is shown that bond graph modelling, although much older, may be viewed as a special form of object-oriented modelling. For that purpose the new object-oriented modelling language Modelica is used as a working language which aims at supporting multiple formalisms. Although it turns out that bond graph models can be described rather easily, it is obvious that Modelica started from generalized networks and was not designed to support bond graphs. The description of bond graph models in Modelica is illustrated by means of a hydraulic drive. Since VHDL-AMS as an important language standardized and supported by IEEE has been extended to support also modelling of non-electrical systems, it is briefly investigated as to whether it can be used for description of bond graphs. It turns out that currently it does not seem to be suitable.
Multidisciplinary systems are described most suitably by bond graphs. In order to determine unnormalized frequency domain sensitivities in symbolic form, this paper proposes to construct in a systematic manner a bond graph from another bond graph, which is called the associated incremental bond graph in this paper. Contrary to other approaches reported in the literature the variables at the bonds of the incremental bond graph are not sensitivities but variations (incremental changes) in the power variables from their nominal values due to parameter changes. Thus their product is power. For linear elements their corresponding model in the incremental bond graph also has a linear characteristic. By deriving the system equations in symbolic state space form from the incremental bond graph in the same way as they are derived from the initial bond graph, the sensitivity matrix of the system can be set up in symbolic form. Its entries are transfer functions depending on the nominal parameter values and on the nominal states and the inputs of the original model. The sensitivities can be determined automatically by the bond graph preprocessor CAMP-G and the widely used program MATLAB together with the Symbolic Toolbox for symbolic mathematical calculation. No particular program is needed for the approach proposed. The initial bond graph model may be non-linear and may contain controlled sources and multiport elements. In that case the sensitivity model is linear time variant and must be solved in the time domain. The rationale and the generality of the proposed approach are presented. For illustration purposes a mechatronic example system, a load positioned by a constant-excitation d.c. motor, is presented and sensitivities are determined in symbolic form by means of CAMP-G/MATLAB.