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Information Channels
(2000)
K3 User Guide
(2000)
his report summarizes the results of a workshop on Groupware related task design which took place at the International Conference on Supporting Group Work Group'99, Arizona, from 14 th to 17 th November 1999.
The workshop was addressed to people from different
viewpoints, backgrounds, and domains:
- Researchers dealing with questions of task analysis
and task modeling for Groupware application from an
academic point of view. They may contribute modelbased design
approaches or theoretically oriented
work
- Practitioners with experience in the design and
everyday use of groupware systems. They might refer
to the practical side of the topic: "real" tasks, "real"
problems, "real" users, etc.
Pressen - Vergleich zwischen Raumlenker- und Exzenterantrieb / Doege, Eckhart ; Engels, Elmar
(1999)
Universelle hydraulische Try-Out Presse / Teilprojekt A6 / Wiendahl, H.-P. ; Doege, E. ; Engels, E.
(1999)
ε-Fe3N has been investigated by time-of-flight neutron diffraction (temperature range 4.2–618 K) and SQUID magnetometry (2–700 K, B≤5 T). A ferromagnetic spin structure is observed with magnetic moments oriented perpendicular to the c-axis of the hexagonal nuclear structure. The magnetic saturation moment of iron is 2.2 μB at 4.2 K from neutron diffraction and 2.0 μB from magnetic measurements and decreases in a Brillouin-like manner on heating to TC=575 K. Above 450 K an increasing but reversible disorder of the nitrogen partial structure is observed.
Making a C2 information system platform independent by using internet and middleware technologies
(1999)
Aim of the AXON2 project (Adaptive Expert System for Object Recogniton using Neuml Networks) is the development of an object recognition system (ORS) capable of recognizing isolated 3d objects from arbitrary views. Commonly, classification is based on a single feature extracted from the original image. Here we present an architecture adapted from the Mixtures of Eaqerts algorithm which uses multiple neuml networks to integmte different features. During tmining each neural network specializes in a subset of objects or object views appropriate to the properties of the corresponding feature space. In recognition mode the system dynamically chooses the most relevant features and combines them with maximum eficiency. The remaining less relevant features arz not computed and do therefore not decelerate the-recognition process. Thus, the algorithm is well suited for ml-time applications.
This paper describes the realization of a novel neurocomputer which is based on the concepts of a coprocessor. In contrast to existing neurocomputers the main interest was the realization of a scalable, flexible system, which is capable of computing neural networks of arbitrary topology and scale, with full independence of special hardware from the software's point of view. On the other hand, computational power should be added, whenever needed and flexibly adapted to the requirements of the application. Hardware independence is achieved by a run time system which is capable of using all available computing power, including multiple host CPUs and an arbitrary number of neural coprocessors autonomously. The realization of arbitrary neural topologies is provided through the implementation of the elementary operations which can be found in most neural topologies.