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Die Durchführung einer systematischen Literaturrecherche ist eine zentrale Kompetenz wissenschaftlichen Arbeitens und bildet daher einen festen Ausbildungsbestandteil von Bachelor- und Masterstudiengängen. In entsprechenden Lehrveranstaltungen werden Studierende zwar mit den grundlegenden Hilfsmitteln zur Suche und Verwaltung von Literatur vertraut gemacht, allerdings werden die Potenziale textanalytischer Methoden und Anwendungssysteme (Text Mining, Text Analytics) dabei zumeist nicht abgedeckt. Folglich werden Datenkompetenzen, die zur systemgestützten Analyse und Erschließung von Literaturdaten erforderlich sind, nicht hinreichend ausgeprägt. Um diese Kompetenzlücke zu adressieren, ist an der Hochschule Osnabrück eine Lehrveranstaltung konzipiert und projektorientiert umgesetzt worden, die sich insbesondere an Studierende wirtschaftswissenschaftlicher Studiengänge richtet. Dieser Beitrag dokumentiert die fachliche sowie technische Ausgestaltung dieser Veranstaltung und zeigt Potenziale für die künftige Weiterentwicklung auf.
Am Beispiel der Telekommunikationsindustrie zeigt der Beitrag eine konkrete Ausgestaltung anwendungsorientierter Forschung, die sowohl für die Praxis als auch für die Wissenschaft nutzen- und erkenntnisbringend ist. Forschungsgegenstand sind die Referenzmodelle des Industriegremiums TM Forum, die von vielen Telekommunikationsunternehmen zur Transformation ihrer Strukturen und Systeme genutzt werden. Es wird die langjährige Forschungstätigkeit bei der Weiterentwicklung und Anwendung dieser Referenzmodelle beschrieben. Dabei wird ein konsequent gestaltungsorientierter Forschungsansatz verfolgt. Das Zusammenspiel aus kontinuierlicher Weiterentwicklung in Zusammenarbeit mit einem Industriegremium und der Anwendung in vielfältigen Praxisprojekten führt zu einer erfolgreichen Symbiose aus praktischer Nutzengenerierung sowie wissenschaftlichem Erkenntnisgewinn. Der Beitrag stellt den gewählten Forschungsansatz anhand konkreter Beispiele vor. Darauf basierend werden Empfehlungen und Herausforderungen für eine gestaltungs- und praxisorientierte Forschung diskutiert.
With the many achievements of Machine Learning in the past years, it is likely that the sub-area of Deep Learning will continue to deliver major technological breakthroughs [1]. In order to achieve best results, it is important to know the various different Deep Learning frameworks and their respective properties. This paper provides a comparative overview of some of the most popular frameworks. First, the comparison methods and criteria are introduced and described with a focus on computer vision applications: Features and Uses are examined by evaluating papers and articles, Adoption and Popularity is determined by analyzing a data science study. Then, the frameworks TensorFlow, Keras, PyTorch and Caffe are compared based on the previously described criteria to highlight properties and differences. Advantages and disadvantages are compared, enabling researchers and developers to choose a framework according to their specific needs.
Design and Development of a Hot S-Parameter Measurement System for Plasma and Magnetron Applications
(2020)
This paper presents the design, development and calibration procedures of a novel hot S-parameter measurement system for plasma and magnetron applications with power level up to 6 kW. Based on a vector network analyzer, a power amplifier and two directional couplers, the input matching hotS 11 and transmission hotS 21 of the device under test are measured at 2.45 GHz center frequency and 300MHz bandwidth, while the device is driven by the magnetron. This measurement system opens a new horizon to develop many new industrial applications such as microwave plasma jets, dryer systems, dryers and so forth. Furthermore, the developing, controlling and monitoring a 2kW 2.45GHz plasma jet and a dryer system using the measurement system are presented and explained.
In this paper we present SMART-FACTORY, a setup for a research and teaching facility in industrial robotics that is based on the RoboCup Logistics League. It is driven by the need for developing and applying solutions for digital production. Digitization receives constantly increasing attention in many areas, especially in industry. The common theme is to make things smart by using intelligent computer technology. Especially in the last decade there have been many attempts to improve existing processes in factories, for example, in production logistics, also with deploying cyber-physical systems. An initiative that explores challenges and opportunities for robots in such a setting is the RoboCup Logistics League. Since its foundation in 2012 it is an international effort for research and education in an intra-warehouse logistics scenario. During seven years of competition a lot of knowledge and experience regarding autonomous robots was gained. This knowledge and experience shall provide the basis for further research in challenges of future production. The focus of our SMART-FACTORY is to create a stimulating environment for research on logistics robotics, for teaching activities in computer science and electrical engineering programmes as well as for industrial users to study and explore the feasibility of future technologies. Building on a very successful history in the RoboCup Logistics League we aim to provide stakeholders with a dedicated facility oriented at their individual needs.
Safety of subjects during radiofrequency exposure in ultra-high-field magnetic resonance imaging
(2020)
Magnetic resonance imaging (MRI) is one of the most important medical imaging techniques. Since the introduction of MRI in the mid-1980s, there has been a continuous trend toward higher static magnetic fields to obtain i.a. a higher signal-to-noise ratio. The step toward ultra-high-field (UHF) MRI at 7 Tesla and higher, however, creates several challenges regarding the homogeneity of the spin excitation RF transmit field and the RF exposure of the subject. In UHF MRI systems, the wavelength of the RF field is in the range of the diameter of the human body, which can result in inhomogeneous spin excitation and local SAR hotspots. To optimize the homogeneity in a region of interest, UHF MRI systems use parallel transmit systems with multiple transmit antennas and time-dependent modulation of the RF signal in the individual transmit channels. Furthermore, SAR increases with increasing field strength, while the SAR limits remain unchanged. Two different approaches to generate the RF transmit field in UHF systems using antenna arrays close and remote to the body are investigated in this letter. Achievable imaging performance is evaluated compared to typical clinical RF transmit systems at lower field strength. The evaluation has been performed under consideration of RF exposure based on local SAR and tissue temperature. Furthermore, results for thermal dose as an alternative RF exposure metric are presented.
Control engineering theory is hard to grasp for undergraduates during the first semesters, as it deals with the dynamical behavior of systems also in combination with control strategies on an abstract level. Therefore, operational amplifier (OpAmp) processes are reasonable and very effective systems to connect mathematical description with actual system’s behavior. In this paper, we present an experiment for a laboratory session in which an embedded system, driven by a LabVIEW human machine interface (HMI) via USB, controls the analog circuits.With this setup we want to show the possibility of firstly, analyzing a first order process and secondly, designing a P-and PI-controller. Thereby, the theory of control engineering is always applied to the empirical results in order to break down the abstract level for the students.