27343383
Anatomische Abbildung elektrischer Aktivität des ZNS
31316829
Restoration of the Sphere-Cortex Homeomorphism
The proposed algorithm has been developed as a pre-processing tool for inflating cortical surface meshes, which have been created using segmentation and subsequent triangulation of magnetic resonance images (MRI) [1]. It works directly on the triangulated surface and is therefore completely independent from the underlying segmentation. It needs no other information than the triangle mesh itself, which makes it generally applicable for the removal of topological noise. The homeomorphism between cortical surface and sphere is re-established by removing handles and opening connections. Moreover, the presented approach guarantees a manifold mesh by locally examining connectivity in the neighbourhood of each vertex and removing non-manifold components. It will be embedded into the source reconstruction software package CURRY (Compumedics Neuroscan, El Paso, TX, USA).
13925823
Context inference of users' social relationships and distributed policy management
Inference of high-level context is becoming crucial in development of context-aware applications. An example is social context inference - i.e., deriving social relations based upon the user's daily communication with other people. The efficiency of this mechanism mainly depends on the method(s) used to draw inferences based on existing evidence and sample information, such as a training data. Our approach uses rule-based data mining, Bayesian network inference, and user feedback to compute the probabilities of another user being in the specific social relationship with a user whose daily communication is logged by a mobile phone. In addition, a privacy mechanism is required to ensure the user's personal integrity and privacy when sharing this user's sensitive context data. Therefore, the derived social relations are used to define a user's policies for context access control, which grant the restricted context information scope depending on the user's current context. Finally, we propose a distributed architecture capable of managing this context information based upon these context access policies.
13891540
MagicMeeting: A Collaborative Tangible Augmented Reality System
We describe an augmented reality (AR) system that allows multiple participants to interact with 2D and 3D data using tangible user interfaces. The system features face-to-face communication, collaborative viewing and manipulation of 3D models, and seamless access to 2D desktop applications within the shared 3D space. All virtual content, including 3D models and 2D desktop windows, is attached to tracked physical objects in order to leverage the efficiencies of natural two-handed manipulation. The presence of 2D desktop space within 3D facilitates data exchange between the two realms, enables control of 3D information by 2D applications, and generally increases productivity by providing access to familiar tools. We present a general concept for a collaborative tangible AR system, including a comprehensive set of interaction techniques, a distributed hardware setup, and a component-based software architecture that can be flexibly configured using XML. We show the validity of our concept with an implementation of an application scenario from the automotive industry.
9212870
Image restoration by fuzzy convex ordinary kriging
Ordinary kriging and fuzzy sets are combined to derive a spatial filter for restoring degraded images. As kriging is a nonconvex estimation technique and negative kriging weights applied to image data can give estimates outside the range of pixel values. Convexity is therefore required in this image analysis to ensure no negative weights. Fuzzy sets are used to enhance the smoothing process of an ordinary kriging filter. Experiments on an image degraded by Gaussian white noise are given to illustrate the effectiveness of the proposed approach in comparison with the adaptive Wiener filter.
1173406
Geschäftsprozeßgestaltung durch Kommunikation und Information
10411388
Large-scale linear programming techniques for the design of protein folding potentials
Abstract.We present large-scale optimization techniques to model the energy function that underlies the folding process of proteins. Linear Programming is used to identify parameters in the energy function model, the objective being that the model predict the structure of known proteins correctly. Such trained functions can then be used either for ab-initio prediction or for recognition of unknown structures. In order to obtain good energy models we need to be able to solve dense Linear Programming Problems with tens (possibly hundreds) of millions of constraints in a few hundred parameters, which we achieve by tailoring and parallelizing the interior-point code PCx.