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Our university carries out various research projects. Among others, the project Schluckspecht is an interdisciplinary work on different ultra-efficient car concepts for international contests. Besides the engineering work, one part of the project deals with real-time data visualization. In order to increase the efficiency of the vehicle, an online monitoring of the runtime parameters is necessary. The driving parameters of the vehicle are transmitted to a processing station via a wireless network connection. We plan to use an augmented reality (AR) application to visualize different data on top of the view of the real car. By utilizing a mobile Android or iOS device a user can interactively view various real-time and statistical data. The car and its components are meant to be augmented by various additional information, whereby that information should appear at the correct position of the components. An engine e.g. could show the current rpm and consumption values. A battery on the other hand could show the current charge level. The goal of this paper is to evaluate different possible approaches, their suitability and to expand our application to other projects at our university.
In the course of the last few years, our students are becoming increasingly unhappy. Sometimes they stop attending lectures and even seem not to know how to behave correctly. It feels like they are getting on strike. Consequently, drop-out rates are sky-rocketing. The lecturers/professors are not happy either, adopting an “I-don’t-care” attitude.
An interdisciplinary, international team set in to find out: (1) What are the students unhappy about? Why is it becoming so difficult for them to cope? (2) What does the “I-don’t-care” attitude of professors actually mean? What do they care or not care about? (3) How far do the views of the parties correlate? Could some kind of mutual understanding be achieved?
The findings indicate that, at least at our universities, there is rather a long way to go from “Engineering versus Pedagogy” to “Engineering Pedagogy”.
Finding clusters in high dimensional data is a challenging research problem. Subspace clustering algorithms aim to find clusters in all possible subspaces of the dataset where, a subspace is the subset of dimensions of the data. But exponential increase in the number of subspaces with the dimensionality of data renders most of the algorithms inefficient as well as ineffective. Moreover, these algorithms have ingrained data dependency in the clustering process, thus, parallelization becomes difficult and inefficient. SUBSCALE is a recent subspace clustering algorithm which is scalable with the dimensions and contains independent processing steps which can be exploited through parallelism. In this paper, we aim to leverage, firstly, the computational power of widely available multi-core processors to improve the runtime performance of the SUBSCALE algorithm. The experimental evaluation has shown linear speedup. Secondly, we are developing an approach using graphics processing units (GPUs) for fine-grained data parallelism to accelerate the computation further. First tests of the GPU implementation show very promising results.
The need to measure basic aerosol parameters has increased dramatically in the last decade. This is due mainly to their harmful effect on the environment and on public health. Legislation requires that particle emissions and ambient levels, workplace particle concentrations and exposure to them are measured to confirm that the defined limits are met and the public is not exposed to harmful concentrations of aerosols.
Applications helping us to maintain the focus on work are called “Zenware” (from concentration and Zen). While form factors, use cases and functionality vary, all these applications have a common goal: creating uninterrupted, focused attention on the task at hand. The rise of such tools exemplifies the users’ desire to control their attention within the context of omnipresent distraction. In expert interviews we investigate approaches in the context of attention-management at the workplace of knowledge workers. To gain a broad understanding, we use judgement sampling in interviews with experts from several disciplines. We especially explore how focus and flow can be stimulated. Our contribution has four components: a brief overview on the state of the art (1), a presentation of the results (2), strategies for coping with digital distractions and design guidelines for future Zenware (3) and an outlook on the overall potential in digital work environments (4).
Gamifying rehabilitation is an efficient way to improve motivation and exercise frequency. However, between flow theory, self-determination theory or Bartle's player types there is much room for speculation regarding the mechanics required for successful gamification, which in turn leads to increased motivation. For our study, we selected a gamified solution for motion training (an exergame) where the playful design elements are extremely simple. The contribution is three-fold: we show best practices from the state of the art, present a study analyzing the effects of simple gamification mechanics on a quantitative and on a qualitative level and discuss strategies for playful design in therapeutic movement games.
In recent years, the additive manufacturing processes have rapidly developed. The additive manufacturing processes currently present a high-performance alternative to conventional manufacturing methods. In particular, they offer the opportunity of previously hardly imaginable design freedom, i.e. the implementation of complex forms and geometries. This capability can, for example, be applied in the development of especially light but still loadable components in automotive engineering. In addition, waste material is seldom produced in additive manufacturing which benefits a sustainable production of building components. Until now, this design freedom was barely used in the construction of technical components and products because, in doing so, both specific design guidelines for additive manufacturing and complex strength calculations must be simultaneously observed. Yet in order to fully take advantage of the additive manufacturing potential, the method of topology optimization, based on FEM simulation, suggests itself. It is with this method that components that are precisely matched and are especially light, thereby also resource-saving, can be produced. Current literature research indicates that this method is used in automotive manufacturing for reducing weight and improving the stability of both individual parts and assembly units. This contribution will study how this development method can be applied in the example of a brake mount from an experimental vehicle. In this, the conventional design is improved by means of a simulation tool for topology optimization in various steps. In an additional processing step, the smoothing of the thus developed component occurs. Finally, the component is generatively manufactured by means of selective laser melting technology. Models are manufactured using binder jetting for the demonstration of the process. It will also be determined how this weight reduction affects the CO2 emissions of a vehicle in use.