Refine
H-BRS Bibliography
- yes (159) (remove)
Departments, institutes and facilities
- Fachbereich Informatik (46)
- Präsidium (35)
- Fachbereich Wirtschaftswissenschaften (25)
- Institute of Visual Computing (IVC) (18)
- Fachbereich Angewandte Naturwissenschaften (17)
- Fachbereich Ingenieurwissenschaften und Kommunikation (17)
- Institut für funktionale Gen-Analytik (IFGA) (12)
- Fachbereich Sozialpolitik und Soziale Sicherung (10)
- Institut für Cyber Security & Privacy (ICSP) (2)
- Institut für Sicherheitsforschung (ISF) (2)
Document Type
- Conference Object (41)
- Article (36)
- Part of Periodical (33)
- Part of a Book (16)
- Book (monograph, edited volume) (11)
- Report (8)
- Master's Thesis (5)
- Bachelor Thesis (3)
- Conference Proceedings (3)
- Contribution to a Periodical (2)
Year of publication
- 2011 (159) (remove)
Keywords
- Unternehmen (3)
- CUDA (2)
- Emergency support system (2)
- Finite-Elemente-Methode (2)
- Mobile sensors (2)
- Robotik (2)
- 3D Crosstalk (1)
- 3D Display (1)
- 3D Visualisierung (1)
- 3D crosstalk (1)
In this paper, the performance evaluation of Frequency Modulated Chaotic On-Off Keying (FM-COOK) in AWGN, Rayleigh and Rician fading channels is given. The simulation results show that an improvement in BER can be gained by incorporating the FM modulation with COOK for SNR values less than 10dB in AWGN case and less than 6dB for Rayleigh and Rician fading channels.
A system that interacts with its environment can be much more robust if it is able to reason about the faults that occur in its environment, despite perfect functioning of its internal components. For robots, which interact with the same environment as human beings, this robustness can be obtained by incorporating human-like reasoning abilities in them. In this work we use naive physics to enable reasoning about external faults in robots. We propose an approach for diagnosing external faults that uses qualitative reasoning on naive physics concepts for diagnosis. These concepts are mainly individual properties of objects that define their state qualitatively. The reasoning process uses physical laws to generate possible states of the concerned object(s), which could result into a detected external fault. Since effective reasoning about any external fault requires the information of relevant properties and physical laws, we associate different properties and laws to different types of faults which can be detected by a robot. The underlying ontology of this association is proposed on the basis of studies conducted (by other researchers) on reasoning of physics novices about everyday physical phenomena. We also formalize some definitions of properties of objects into a small framework represented in First-Order logic. These definitions represent naive concepts behind the properties and are intended to be independent from objects and circumstances. The definitions in the framework illustrates our proposal of using different biased definitions of properties for different types of faults. In this work, we also present a brief review of important contributions in the area of naive/qualitative physics. These reviews help in understanding the limitations of naive/qualitative physics in general. We also apply our approach to simple scenarios to asses its limitations in particular. Since this work was done independent of any particular real robotic system, it can be seen as a theoretical proof of the concept of usefulness of naive physics for external fault reasoning in robotics.
Despite perfect functioning of its internal components, a robot can be unsuccessful in performing its tasks because of unforeseen situations. These situations occur when the behavior of the objects in the robot’s environment deviates from its expected values. For robots, such deviations are exhibited in the form of unknown external faults which prohibit them from performing their tasks successfully. In this work we propose to use naive physics knowledge to reason about such faults in the robotics domain. We propose an approach that uses naive physics concepts to find information about the situations which result in a detected unknown fault. The naive physics knowledge is represented by the physical properties of objects which are formalized in a logical framework. The proposed approach applies a qualitative version of physical laws to these properties for reasoning about the detected fault. By interpreting the reasoning results the robot finds the information about the situations which can cause the fault. We apply the proposed approach to the scenarios in which a robot performs manipulation tasks of picking and placing objects. Results of this application show that naive physics holds great promise for reasoning about unknown ex- ternal faults in robotics.
Nowadays, we input text not only on stationary devices, but also on handheld devices while walking, driving, or commuting. Text entry on the move, which we term as nomadic text entry, is generally slower. This is partially due to the need for users to move their visual focus from the device to their surroundings for navigational purposes and back. To investigate if better feedback about users' surroundings on the device can improve performance, we present a number of new and existing feedback systems: textual, visual, textual & visual, and textual & visual via translucent keyboard. Experimental comparisons between the conventional and these techniques established that increased ambient awareness for mobile users enhances nomadic text entry performance. Results showed that the textual and the textual & visual via translucent keyboard conditions increased text entry speed by 14% and 11%, respectively, and reduced the error rate by 13% compared to the regular technique. The two methods also significantly reduced the number of collisions with obstacles.
Die Komplexität der Entscheidungen im Fuhrparkmanagement hat in der jüngeren Vergangenheit deutlich zugenommen. Damit steigen die Anforderungen an den Fuhrparkcontroller, den Fuhrparkleiter mit entscheidungsrelevanten Informationen im Sinne eines internen Dienstleisters zu unterstützen. Das Dynamic Carbon Accounting bietet die Möglichkeit, strategische, strukturelle und kulturelle Anforderungen an das Fuhrparkcontrolling durch die Kombination von Prozesskostenrechnung, Target Costing, Life Cycle Costing und den Ideen des Carbon Accountings instrumentell zu berücksichtigen. Je nach Bedeutung der Nachhaltigkeit für den Unternehmenserfolg können die damit verbundenen Auszahlungen noch differenzierter aufgenommen werden. So ist es denkbar, externe Auszahlungen der Emissionen von NO(ind x), Nichtmethan-Kohlenwasserstoffen, Partikeln, Lärm und Unfällen in die Rechnung zu integrieren. Damit wird je Fahrzeug der Beitrag zur Erreichung von Emissionszielen transparent gemacht und ist durch eine zielgerichtete Integration in den Controllingprozess des Unternehmens plan- und steuerbar. Da von einer zukünftig zunehmenden Komplexität des wirtschaftlichen Handelns auszugehen ist, wird sich der praktische Bedarf an dynamischen, marktorientierten Instrumenten im Controlling generell und speziell im Fuhrparkcontrolling weiter erhöhen.
Der I. Senat des BFH hat dem Großen Senat mit Beschluss vom 7.4.2010 die Frage vorgelegt, ob der subjektive Fehlerbegriff zwar in Bezug auf nach Bilanzaufstellung neu bekanntgewordene Tatsachen beizubehalten, in Bezug auf bessere Rechtserkenntnisse nach Bilanzaufstellung aber aufzugeben ist. Der Große Senat hat insoweit eine schwierige Entscheidung zu treffen, da sich materielles Bilanzsteuerrecht, Verfahrensrecht und Handelsrecht bei dieser Frage überlagern. hat schon 1991 von einem heillosen und verworrenen Labyrinth gesprochen, in dem es schwer falle, die Prinzipien zu erkennen. Zusätzlich hat der Große Senat unter dem Gesichtspunkt der Kontinuität der Rechtsprechung und der Rechtssicherheit abzuwägen, ob es gerechtfertigt ist, eine seit 50 Jahren bestehende Rechtsprechung aufzugeben. Die Entscheidung des Großen Senats hat sich durch den Präsidentenwechsel beim BFH verzögert, ist aber nunmehr in nächster Zeit zu erwarten.
This thesis work presents the implementation and validation of image processing problems in hardware to estimate the performance and precision gain. It compares the implementation for the addressed problem on a Field Programmable Gate Array (FPGA) with a software implementation for a General Purpose Processor (GPP) architecture. For both solutions the implementation costs for their development is an important aspect in the validation. The analysis of the flexibility and extendability that can be achieved by a modular implementation for the FPGA design was another major aspect. This work is based upon approaches from previous work, which included the detection of Binary Large OBjects (BLOBs) in static images and continuous video streams [13, 15]. One addressed problem of this work is the tracking of the detected BLOBs in continuous image material. This has been implemented for the FPGA platform and the GPP architecture. Both approaches have been compared with respect to performance and precision. This research project is motivated by the MI6 project of the Computer Vision research group, which is located at the Bonn-Rhein-Sieg University of Applied Sciences. The intent of the MI6 project is the tracking of a user in an immersive environment. The proposed solution is to attach a light emitting device to the user for tracking the created light dots on the projection surface of the immersive environment. Having the center points of those light dots would allow the estimation of the user’s position and orientation. One major issue that makes Computer Vision problems computationally expensive is the high amount of data that has to be processed in real-time. Therefore, one major target for the implementation was to get a processing speed of more than 30 frames per second. This would allow the system to realize feedback to the user in a response time which is faster than the human visual perception. One problem that comes with the idea of using a light emitting device to represent the user, is the precision error. Dependent on the resolution of the tracked projection surface of the immersive environment, a pixel might have a size in cm2. Having a precision error of only a few pixels, might lead to an offset in the estimated user’s position of several cm. In this research work the development and validation of a detection and tracking system for BLOBs on a Cyclone II FPGA from Altera has been realized. The system supports different input devices for the image acquisition and can perform detection and tracking for five to eight BLOBs. A further extension of the design has been evaluated and is possible with some constraints. Additional modules for compressing the image data based on run-length encoding and sub-pixel precision for the computed BLOB center-points have been designed. For the comparison of the FPGA approach for BLOB tracking a similar implementation in software using a multi-threaded approach has been realized. The system can transmit the detection or tracking results on two available communication interfaces, USB and RS232. The analysis of the hardware solution showed a similar precision for the BLOB detection and tracking as the software approach. One problem is the strong increase of the allocated resources when extending the system to process more BLOBs. With one of the applied target platforms, the DE2-70 board from Altera, the BLOB detection could be extended to process up to thirty BLOBs. The implementation of the tracking approach in hardware required much more effort than the software solution. The design of high level problems in hardware for this case are more expensive than the software implementation. The search and match steps in the tracking approach could be realized more efficiently and reliably in software. The additional pre-processing modules for sub-pixel precision and run-length-encoding helped to increase the system’s performance and precision.