Projekte

2012

  • AUTOMEX – Automatische Extraktion von Mittelflächenbeschreibungen aus 3D-CAD-Volumenmodellen.

 

2010

  • primaboinca : Dieses Projekt befasst sich mit zwei Hypothesen aus dem Bereich der Zahlentheorie. Hierbei handelt es sich jeweils um Vermutungen zur Identifizierung von Primzahlen. Die erste Vermutung (Agrawals Vermutung) war Ausgangspunkt zur Formulierung des ersten deterministischen Primzahltestalgorithmus mit polynomialer Laufzeit (AKS-Algorithmus).
    Hendrik Lenstras und Carl Pomerances Heuristik zu dieser Vermutung legt nahe, dass es unendlich viele Gegenbeispiele geben müsste. Jedoch ist bis dato kein Gegenbeispiel bekannt. Diese Hypothese wurde für n < 1010 überprüft, ohne ein Gegenbeispiel zu finden. Die zweite Vermutung (Popovychs Vermutung) ergänzt Agrawals Vermutung um eine weitere Bedingung und stellt somit eine logische Verstärkung der Vermutung dar. Sollte eine dieser Hypothesen stimmen, würde die Laufzeit vom AKS-Algorithmus von O(log N)6 (aktuell schnellste Version des AKS-Algorithmus) zu O(log N)3 reduziert werden.
    Auf Grundlage mathematischer Aussagen aus beiden Vermutungen wurde in dieser Arbeit ein Algorithmus zur Suche nach einem Gegenbeispiel formuliert. Um über mehr Rechenleistung zu verfügen und somit einen größeren Zahlenbereich überprüfen zu können, wurde ein Algorithmus zum verteilten Rechnen implementiert. Hierzu wurden zwei Architekturtypen untersucht: eine Grid-Computing- und eine Volunteer-Computing-Architektur.
    Bedingt durch die Voruntersuchungen erscheint der Grid-Computing Ansatz nicht attraktiv, da der Zugang zu den nötigen Ressourcen mit zu großem zeitlichen Aufwand verbunden ist. Aus diesem Grund wurde der Fokus auf den Volunteer-Computing-Ansatz gelegt. Als Implementierung dieser Architektur wurde das quelloffene Berkeley Open Infrastructure for Network Computing (kurz BOINC) verwendet. Hierbei sind eine Linux-, Windows- und Cell BE-Version entstanden, um das Rechnen auf unterschiedlichen Plattformen und Vergleiche zwischen diesen zu ermöglichen.[/caption]

2009

  • VotKA : (Visualization of the k-means Algorithm) a project of the course Visualization in the Master’s studies of Computer Sciences at the RheinMain University of Applied Sciences. This project is a 3D visualization of the k-means algorithm applied to Fisher’s dataset. The user can interact with the visualization via reacTIVision/Fiducials or the OSCRemote application on the iPhone/iPod Touch.
    3D scatter plot of Fisher’s dataset assorted with the k-means algorithm

    In VotkA users can interact with a three-dimensional cluster analysis visualization via a Tangible User Interface (TUI), the iPhone app OSCRemote or both in parallel. The TUI is provided by a small box that is technically based on Seth Sandler’s cheap multi-touch pad (you can see the box in the youtube video at the end of this article). On top of the box fiducials from reacTIVision are being tracked. Whenever a fiducial is being recognized a TUIO message with the fiducial’s id, position and rotation will be sent to VotkA.

    In terms of the cluster analysis the k-means algorithm has been implemented. The underlying multivariate data that is being visualized is Fisher’s iris dataset. In this dataset different aspects of iris blossoms are being stored (e.g. petal length/width, sepal length/width). Within the visualization this data is being dispersed in a cube according to different aspects (e.g. on the x-axis petal length, on the y axis sepal width and on the y-axis sepal height).

    The implemented visualization methods 3D scatter plot (see figure), scatter plot matrix / Grand Tour have been slightly adjusted to visualize Fisher’s dataset. The interaction with the Grand Tour visualization method is being carried out in the TUI with a real cube, which incorporates the projection of the three-dimensional data on the dimensional layers in the graph. By tilting the cube in the application the appropriate projection side will be displayed on the screen.

    When interacting via fiducials an additional sound feedback mechanism has been provided by converting TUIO messages in VotkA to midi signals that are being sent to a software sequencer. Midi channels are mapped to fiducial ids and midi signals are produced according to position and rotation of the fiducials. Actually it should not have been necessary to convert TUIO messages in VotkA to midi because reacTIVision supports both outputs, midi and TUIO. However, only one output channel at a time can be handled by reacTIVision.

    Video of interaction with VotkA. Please note that colors are being poorly displayed and that midi sound output has been disabled in this video:


    3D scatter plot of Fisher’s dataset assorted with the k-means algorithm

 

2008

  • AKS@CBE

2007

  • TimeTube : In an analytical laboratory, the scheduling of which assays are analyzed in which order and on which laboratory resources is a good example for a task that cannot be solved by a computer system alone. A computer system implementing scheduling algorithms, however, can be used to support the laboratory staff in order to find suitable schedules serving in a sense as an intelligence amplification tool for the human user. For this, the user interface is crucial and we employ a novel visualization technique we call TimeTube in order to enable the user to easily grasp the current state of the scheduling process and to facilitate decisions on how to optimize the schedule. In order to interact with the 3D visualization that we have conceived, a pen-shaped force-feedback device, the commercially available „Phantom Omni„, is used.
    TimeTube + Phantom Omni

    It serves not only as a means for 3D input but is also able to provide haptic guidance. And it makes constraints on the schedule intuitively perceivable, by realizing a „haptic visualization“. We present a prototype system that implements the TimeTube technique and integrates it with a sophisticated scheduler.

    TimeTube combines findings of ...

    First test results show that completing tasks and navigating through time is intuitive for the users. As such, the system is a best practice example for a problem solver that takes advantage of the strengths of humans and computers.