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The work being described in this paper is the result of a cooperation project between the Institute of Visual Computing at the Bonn-Rhein-Sieg University of Applied Sciences, Germany and the Laboratory of Biomedical Engineering at the Federal University of Uberlândia, Brazil. The aim of the project is the development of a virtual environment based training simulator which enables for better and faster learning the control of upper limb prostheses. The focus of the paper is the description of the technical setup since learning tutorials still need to be developed as well as a comprehensive evaluation still needs to be carried out.
Augmented Perception - AuPer
(2004)
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.
The objective of the presented approach is to develop a 3D-reconstruction method for micro organisms from sequences of microscopic images by varying the level-of-focus. The approach is limited to translucent silicatebased marine and freshwater organisms (e.g. radiolarians). The proposed 3D-reconstruction method exploits the connectivity of similarly oriented and spatially adjacent edge elements in consecutive image layers. This yields a 3D-mesh representing the global shape of the objects together with details of the inner structure. Possible applications can be found in comparative morphology or hydrobiology, where e.g. deficiencies in growth and structure during incubation in toxic water or gravity effects on metabolism have to be determined.
This paper describes adaptive time frequency analysis of EEG signals, both in theory as well as in practice. A momentary frequency estimation algorithm is discussed and applied to EEG time series of test persons performing a concentration experiment. The motivation for deriving and implementing a time frequency estimator is the assumption that an emotional change implies a transient in the measured EEG time series, which again are superimposed by biological white noise as well as artifacts. It will be shown how accurately and robustly the estimator detects the transient even under such complicated conditions.