Zacharias, terHorst et al. (Hg.): Forschungsspitzen und Spitzenforschung. Innovationen an der FH Bonn-Rhein-Sieg, Festschrift für Wulf Fischer
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The ongoing miniaturization, multi-layer structure parts and hybrid parts require methods to determine mechanical properties on a micro-scale. However, there is a gap in measuring techniques. On one hand there are the classical methods to measure hardness e.g. VICKERS, ROCKWELL, UNIVERSAL, IRHD etc having resolutions typically above 100μm. On the other hand there are well-developed AFM methods that allow for the determination of mechanical properties in the nanometer range. This paper describes an indentation technique that yields data of mechanical properties in the micrometer range between typically 5 to 50 μm. The measuring device and the data evaluation is presented. Results of micro-mechanical mapping are shown for NR-SBR rubber interfaces, a fuel tank and a part manufactured by two component injection moulding. Finally, the measured micro-mechanical stiffness is compared to the YOUNG’s modulus of the corresponding materials.
With regard to performance well established SW-only design methodologies proceed by making the initial specification run first, then by enhancing its functionality and finally by optimizing it. When designing Embedded Systems (EbS) this approach is not viable since decisive design decisions like e.g. the estimation of required processing power or the identification of those parts of the specification which need to be delegated to dedicated HW depend on the fastness and fairness of the initial specification. We here propose a sequence of optimization steps embedded into the design flow, which enables a structured way to accelerate a given working EbS specification at different layers. This sequence of accelerations comprises algorithm selection, algorithm transformation, data transformation, implementation optimization and finally HW acceleration. It is analyzed how all acceleration steps are influenced by the specific attributes of the underlying EbS. The overall acceleration procedure is explained and quantified at hand of a real-life industrial example.
A method for the identification of polymeric residues in recycled aluminium by using analytical pyrolysis at 700°C hyphenated to gas chromatography-mass spectrometry (Py-GC/MS) was presented for the first time. The polymeric residues in recycled aluminium were identified as a mixture of polyethylene, polystyrene, and phenolic resin. The described method could be useful for the aluminium industry as a part of the quality control of the recycled aluminium production.
In the presented project, a new approach for the prevention of hand movements leading to hazards and for non-contact detection of fingers is intended to permit comprehensive and economical protection on circular saws. The basic principles may also be applied to other machines with manual loading and / or unloading. With an automatic blade guard an improved integration of the protection system can be achieved. In addition a new detection principle is explained. The distinction between skin and wood or other material is achieved by a dedicated spectral analysis in the near infrared region. Using LED and photodiodes it is possible to detect fingers and hands reliably. With a kind of light curtain the intrusion of hands or fingers into the dangerous zone near the blade guard can be prevented.
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 visualisation environment which provides visual data relative to the motion and activity of the test bicycle. That means the bike rider has to pedal and steer the bicycle as a usual bicycle, while the motion is recorded and processed to control the simulation. 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 match to the virtual environment and the reaction of the driver (e.g. steering angle, step rate).
Motivation is a key ingredient for learning: Only if the learner is motivated, successful learning is possible. Educational robotics has proven to be an excellent tool for motivating students at all ages from 8 to 80. Robot competitions for kids, like RoboCupJunior, are instrumental to sustain motivation over a significant period of time. This increases the chances that the learner acquires more in-depth knowledge about the subject area and develops a genuine interest in the field.
Gas chromatography with flame-ionization detection (FID) and gas chromatography-mass spectrometry (GC/MS) has been used for structure elucidation of long-chain primary n-alkyl amines after derivatization with trifluoroacetic anhydride (TFAA). Electron impact ionization- (EI) and positive chemical ionization- (PCI) mass spectra of trifluoroacetylated derivatives of the identified nalkyl amines are presented. The corrosion inhibiting n-alkyl amines were applied in the investigation of a new anticorrosive and antifouling formulation for water-steam circuit of energy systems in the power industry. The presented results are part of an EU-funded international collaboration with partners from research institutes and industry from Poland, Lithuania, Romania, France and Germany (EUREKA project BOILTREAT E!2426).
In Artificial Intelligence, numerous learning paradigms have been developed over the past decades. In most cases of embodied and situated agents, the learning goal for the artificial agent is to „map“ or classify the environment and the objects therein [1, 2], in order to improve navigation or the execution of some other domain-specific task. Dynamic environments and changing tasks still pose a major challenge for robotic learning in real-world domains. In order to intelligently adapt its task strategies, the agent needs cognitive abilities to more deeply understand its environment and the effects of its actions. In order to approach this challenge within an open-ended learning loop, the XPERO project (http://www.xpero.org) explores the paradigm of Learning by Experimentation to increase the robot's conceptual world knowledge autonomously. In this setting, tasks which are selected by an actionselection mechanism are interrupted by a learning loop in those cases where the robot identifies learning as necessary for solving a task or for explaining observations. It is important to note that our approach targets unsupervised learning, since there is no oracle available to the agent, nor does it have access to a reward function providing direct feedback on the quality of its learned model, as e.g. in reinforcement learning approaches. In the following sections we present our framework for integrating autonomous robotic experimentation into such a learning loop. In section 1 we explain the different modules for stimulation and design of experiments and their interaction. In section 2 we describe our implementation of these modules and how we applied them to a real world scenario to gather target-oriented data for learning conceptual knowledge. There we also indicate how the goaloriented data generation enables machine learning algorithms to revise the failed prediction model.
A soluble form of the complement receptor CD21 (sCD21) is shed from the lymphocyte surface. The sCD21 is able to bind all known ligands such as CD23, sCD23, Epstein-Barr virus and C3d in immune complexes. Here, we show the serum levels of sCD21 in sera the of antiphospholipid syndrome (APS) patients. Antiphospholipid syndrome is an autoimmune disorder in which autoantibodies cause heart attack, stroke and miscarriage. Antiphospholipid syndrome may appear as primary or in association with systemic lupus erythromatosus (SLE) and other autoimmune diseases. Here, we ask whether APS patients have different sCD21 titers compared to healthy persons and whether sCD21 levels correlate with the presence of anti-β2-GPI autoantibodies. We show that autoimmune APS patients have significantly reduced amounts of sCD21 in their sera, irrespective of the presence of anti-β2-GPI autoantibodies. In our APS patients cohort additional SLE, vasculities, DVT (deep vein thrombosis), fetal loss or thrombosis did not correlate to the reduced level of sCD21.
Embryonic stem cells (ES) have the potential of long-term viability, selfrenewal and pluripotency which makes them interesting candidates for tissue engineering and gene therapy applications. On the other hand ethical and political issues arise while using theses cells and severe problems such as their tumorgenicity have not been solved yet. In the last couple of month a new source of cells with stem cell character was developed, the induced pluripotent stem cells (iPS). These cells are derived from differentiated adult cells via transduction of three transcription factors and show features similar to embryonic stem cells. Unfortunately, this includes the tumorgenicity which is even higher in those cells since the transcription factor transduction needed until now, is performed with retrovial vectors, which have a tumor potential on their own. Thus, adult stem cells are investigated extensively as alternative source of self-renewing cells. Human mesenchymal stem cells (HMSCs), which have in addition the advantage of potential autologous transplantation, can be found in various differentiated tissues since they are needed for maintenance and repair. They can be differentiated in chondrogenic, osteogenic, adipogenic and myogenic lineages which makes them an excellent tool for future tissue replacement strategies.
Timely recognition of threats can be significantly supported by security assistance systems that work continuously in time and call the security personnel in case of anomalous events in the surveillance area. We describe the concept and the realization of an indoor security assistance system for real-time decision support. The system consists of a computer vision module and a person classification module. The computer vision module provides a video event analysis of the entrance region in front of the demonstrator. After entering the control corridor, the persons are tracked, classified, and potential threats are localized inside the demonstrator. Data for the person classification are provided by chemical sensors detecting hazardous materials. Due to their limited spatio-temporal resolution, a single chemical sensor cannot localize this material and associate it with a person. We compensate this deficiency by fusing the output of multiple, distributed chemical sensors with kinematical data from laser-range scanners. Considering both the computer vision formation and the results of the person classification affords the localization of threats and a timely reaction of the security personnel.
In the last 5 years a close co-operation between the Bonn-Rhein-Sieg University of Applied Sciences and the Philips Research Laboratories in Aachen has been established. In this article I want to report on the co-operation of the Department of Electrical Engineering, Mechanical Engineering and Technical Journalism with Philips. Besides a number of diploma theses on the field of water treatment with new discharge lamps, power electronics and modelling of electromagnetic field configurations, there is running also an activity on a new generation of highly efficient light sources based on molecular discharges.