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We propose a new alignment procedure that is capable of aligning protein sequences and structures in a unified manner. Recursive dynamic programming (RDP) is a hierarchical method which, on each level of the hierarchy, identifies locally optimal solutions and assembles them into partial alignments of sequences and/or structures. In contrast to classical dynamic programming, RDP can also handle alignment problems that use objective functions not obeying the principle of prefix optimality, e.g.\ scoring schemes derived from energy potentials of mean force. For such alignment problems, RDP aims at computing solutions that are near-optimal with respect to the involved cost function and biologically meaningful at the same time. Towards this goal, RDP maintains a dynamic balance between different factors governing alignment fitness such as evolutionary relationships and structural preferences. As in the RDP method gaps are not scored explicitly, the problematic assignment of gap cost parameters is circumvented. In order to evaluate the RDP approach we analyse whether known and accepted multiple alignments based on structural information can be reproduced with the RDP method. For this purpose, we consider the family of ferredoxins as our prime example. Our experiments show that, if properly tuned, the RDP method can outperform methods based on classical sequence alignment algorithms as well as methods that take purely structural information into account.
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.
GL-Wrapper for Stereoscopic Rendering of Standard Applications for a PC-based Immersive Environment
(2007)
Augmented Perception - AuPer
(2004)
This paper presents an overview on and reports on early experiences of the European ACTS project AC089 called „Distributed Video Production (DVP)“ which started in late 1995. Central to DVP are distributed pilot applications for professional digital video production over ATM broadband networks (LAN and WAN). Distributed video production refers to situations where the cameras, recorders, switches, mixers and other equipment used in video production (or post-production) are located at several sites linked by high bandwidth network connections. The DVP project investigates requirements of broadcasters for several forms of distributed video production and runs a series of trials of distributed virtual studios, distributed rehearsals and remote video editing and retrieval. Together with North American partners a transatlantic broadband ATM link will be tested for distributed virtual reality simulations. This paper reports about two initial tests with a German public broadcaster and the German Telekom. DVP project partners are GMD and about 20 broadcasters, computer and video equipment manufacturers, and video production companies. More information can be obtained from http://viswiz.gmd.de/DVP
The objective of the FIVIS project is to develop a bicycle simulator which is able to simulate real life bicycle ride situations as a virtual scenario within an immersive environment. A sample test bicycle is mounted on a motion platform to enable a close to reality simulation of turns and balance situations. The visual field of the bike rider is enveloped within a multi-screen visualization environment which provides visual data relative to the motion and activity of the test bicycle. This implies the bike rider has to pedal and steer the bicycle as they would a traditional bicycle, while forward motion is recorded and processed to control the visualization. Furthermore, the platform is fed with real forces and accelerations that have been logged by a mobile data acquisition system during real bicycle test drives. Thus, using a feedback system makes the movements of the platform reflect the virtual environment and the reaction of the driver (e.g. steering angle, step rate).
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.