Fachbereich Ingenieurwissenschaften und Kommunikation
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Cost efficient energy monitoring in existing large buildings demands for autonomous indoor sensors with low power consumption, high performance in multipath fading channels and economic implementation. Good performance in multipath fading channels can be achieved with noncoherent chaotic modulation schemes such as chaos on-off keying (COOK) or differential chaos shift keying (DCSK). While COOK stands out in the area of power consumption, DCSK excels when it comes to its performance in noisy and multipath fading channels. This paper evaluates a combination of both schemes for autonomous indoor sensors. The simulation results show 50% less power consumption than DCSK and more than 3dB SNR gain in Rayleigh fading channels at BER=10-3 as compared to COOK, making it a promising candidate for low power transmission in autonomous wireless indoor sensors. We further present an enhanced version of this scheme showing another 1 dB SNR improvement, but at 25% less power consumption than DCSK.
Using an Embroidery Machine to Achieve a Deeper Understanding of Electromechanical Applications
(2013)
Der Wechsel vom Lehren zum aktiven Lernen kann durch studentische Projekte gelingen. Studierende wenden das bisher vermittelte Wissen an und erleben dadurch Ihre eigene Handlungskompetenz während der Bearbeitung einer berufsnahen Aufgabenstellung. Lernziel ist hierbei die Steigerung der Handlungskompetenz, bestehend aus Fach-, Sozial-, Methoden- und Individualkompetenz durch die Aufgabenbearbeitung im Team. Insbesondere wird dabei auch Wert auf die Vermittlung und Erfahrung von Skills, wie z. B. Kooperationsfähigkeit, Kommunikationsverhalten und Arbeitsorganisation gelegt.
Qualitätsverbesserung und Zeitersparnis bei der Stipendienvergabe durch automatisierten Workflow
(2013)
Für die Vergabe der Deutschlandstipendien hatte die Hochschule anfangs ein Verfahren festgelegt, das viel manuelle Arbeitsschritte umfasst: Die Studierenden hatten ihre Bewerbungsunterlagen schriftlich einzureichen. Dazu gehörten neben einem Motivationsschreiben, einem Ausdruck des aktuellen Notenspiegels alle weiteren Referenzen zur Einschätzung der Bewerbung gemäß den gesetzlichen Auswahlkriterien. Als Grundlage zur Bewertung der „sozialen Kriterien“ sollten die Bewerberinnen und Bewerber ein Gutachten eines Professors oder einer Professorin der Hochschule einholen.
Für kleinere Unternehmen mit geringen Ressourcen ist die Gestaltung des QM-Systems eine beträchtliche Herausforderung: Welche Methoden und Maßnahmen sind nötig und bestgeeignet, um die Qualitätskosten nachhaltig zu senken? Durch individuelle und ganzheitliche Betrachtung des Unternehmens sowie Einsatz der Kraftfeldanalyse gelang es einem Metallverarbeiter, ein maßgeschneidertes und dauerhaft wirksames QM-System zu implementieren.
Mathematische Vorkurse werden zur Vorbereitung auf das Studium allen Studienanfängerinnen und Studienanfängern der Ingenieurmathematik dringend empfohlen, aber leider fällt es immer schwerer, die Lücke zwischen den Erwartungen an die Vorkenntnisse der Studierenden und dem tatsächlichen Rüstwerkzeug der Studienanfänger/innen zu schließen. In diesem Artikel wird die Projektidee vorgestellt, im Rahmen einer Zusammenarbeit mit dem internationalen ROLE-Projekt einen mathematischen Vorkurs durch zusätzliche Elemente aus dem Bereich der Open Educational Resources sinnvoll zu ergänzen, um eine Binnendifferenzierung zu ermöglichen und den Studierenden zu erleichtern, sich in den Lehrstoff individuell einzuarbeiten.
When it comes to university-level mathematics in engineering education it is getting harder and harder to bridge the gap between the requirements of the curriculum and the actual math skills of first-year students. Often students fail to realise that they lack elementary math skills. Lecturers intend to help them to learn what they have not learned at school. But obstacles like for example lapses in their concentration while working on exercises or playing down their problems can make it difficult to bridge existing gaps.
In order to increase the concentration while solving problems that deal with elementary mathematics students could communicate in a foreign language. By doing so, they have to understand the subject matter in order to talk about it. The Bonn-Rhein-Sieg University of Applied Science tries to launch a project that examines how dealing with these mathematical problems in a foreign language can support students acquiring fundamental mathematical skill. For this purpose the university is seeking for an international partnership. Via virtual communications students from both universities work in teams in English on mathematical problems. The research question if foreign language teaching can advance the acquisition of knowledge is the focus of interest.
The simulation of fluid flows is of importance to many fields of application, especially in industry and infrastructure. The modelling equations applied describe a coupled system of non-linear, hyperbolic partial differential equations given by one-dimensional shallow water equations that enable the consistent implementation of free surface flows in open channels as well as pressurised flows in closed pipes. The numerical realisation of these equations is complicated and challenging to date due to their characteristic properties that are able to cause discontinuous solutions.
Molecular modeling is an important subdomain in the field of computational modeling, regarding both scientific and industrial applications. This is because computer simulations on a molecular level are a virtuous instrument to study the impact of microscopic on macroscopic phenomena. Accurate molecular models are indispensable for such simulations in order to predict physical target observables, like density, pressure, diffusion coefficients or energetic properties, quantitatively over a wide range of temperatures. Thereby, molecular interactions are described mathematically by force fields. The mathematical description includes parameters for both intramolecular and intermolecular interactions. While intramolecular force field parameters can be determined by quantum mechanics, the parameterization of the intermolecular part is often tedious. Recently, an empirical procedure, based on the minimization of a loss function between simulated and experimental physical properties, was published by the authors. Thereby, efficient gradient-based numerical optimization algorithms were used. However, empirical force field optimization is inhibited by the two following central issues appearing in molecular simulations: firstly, they are extremely time-consuming, even on modern and high-performance computer clusters, and secondly, simulation data is affected by statistical noise. The latter provokes the fact that an accurate computation of gradients or Hessians is nearly impossible close to a local or global minimum, mainly because the loss function is flat. Therefore, the question arises of whether to apply a derivative-free method approximating the loss function by an appropriate model function. In this paper, a new Sparse Grid-based Optimization Workflow (SpaGrOW) is presented, which accomplishes this task robustly and, at the same time, keeps the number of time-consuming simulations relatively small. This is achieved by an efficient sampling procedure for the approximation based on sparse grids, which is described in full detail: in order to counteract the fact that sparse grids are fully occupied on their boundaries, a mathematical transformation is applied to generate homogeneous Dirichlet boundary conditions. As the main drawback of sparse grids methods is the assumption that the function to be modeled exhibits certain smoothness properties, it has to be approximated by smooth functions first. Radial basis functions turned out to be very suitable to solve this task. The smoothing procedure and the subsequent interpolation on sparse grids are performed within sufficiently large compact trust regions of the parameter space. It is shown and explained how the combination of the three ingredients leads to a new efficient derivative-free algorithm, which has the additional advantage that it is capable of reducing the overall number of simulations by a factor of about two in comparison to gradient-based optimization methods. At the same time, the robustness with respect to statistical noise is maintained. This assertion is proven by both theoretical considerations and practical evaluations for molecular simulations on chemical example substances.
Power train models are required to simulate hence predict energy consumption of vehicles. Efficiencies for different components in power train are required. Common procedures use digitalised shell models (or maps) to model the efficiency of Internal Combustion Engines (ICE) and manual gearboxes (MG). Errors are connected with these models and affect the accuracy of the calculation. The accuracy depends on the configuration of the simulation, the digitalisation of the data and the data used. This paper evaluates these sources of error. The understanding of the source of error can improve the results of the modelling by more than eight percent.