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The initial idea of Robotic Process Automation (RPA) is the automation of business processes through a simple emulation of user input and output by software robots. Hence, it can be assumed that no changes of the used software systems and existing Enterprise Architecture (EA) is
required. In this short, practical paper we discuss this assumption based on a real-life implementation project. We show that a successful RPA implementation might require architectural work during analysis, implementation, and migration. As practical paper we focus on exemplary lessons-learned and new questions related to RPA and EA.
Wie real ist unsere Realität? Wie »wirklich« ist das, was wir wahrnehmen und wie »wahr« kann die »Wahrheit« eigentlich sein? Medial vermittelte Informationen spielen für den Prozess der Meinungsbildung eine entscheidende Rolle. In der Wanderausstellung real:ly? geht es um einen Perspektivwechsel. Am Beispiel der »Atomwaffentests auf den Marshallinseln« wird das medial erzeugte Bild amerikanischer Berichterstattung persönlichen Geschichten der Marshaller*innen gegenübergestellt: Technologischer Fortschritt, das Wettrüsten mit der UdSSR und die Macht über die Atombombe treffen auf Erzählungen über Zwangsumsiedlung, Krankheit, Ausbeutung und Abhängigkeit. real:ly? soll daran erinnern, die andere Seite der Medaille zu bedenken und eine andere Perspektive einzunehmen, bevor man seine Meinung bildet. Denn alles, was wir zu wissen glauben, ist nur ein kleiner Teil der ganzen Geschichte.
Anyone who has always wanted to understand the hieroglyphs on Sheldon's blackboard in the TV series The Big Bang Theory or who wanted to know exactly what the fate of Schrödinger's cat is all about will find a short, descriptive introduction to the world of quantum mechanics in this essential. The text particularly focuses on the mathematical description in the Hilbert space. The content goes beyond popular scientific presentations, but is nevertheless suitable for readers without special prior knowledge thanks to the clear examples.
This paper presents the laser-based powder bed fusion (L-PBF) using various glass powders (borosilicate and quartz glass). Compared to metals, these require adapted process strategies. First, the glass powders were characterized with regard to their material properties and their processability in the powder bed. This was followed by investigations of the melting behavior of the glass powders with different laser wavelengths (10.6 µm, 1070 nm). In particular, the experimental setup of a CO2 laser was adapted for the processing of glass powder. An experimental setup with integrated coaxial temperature measurement/control and an inductively heatable build platform was created. This allowed the L-PBF process to be carried out at the transformation temperature of the glasses. Furthermore, the component’s material quality was analyzed on three-dimensional test specimen with regard to porosity, roughness, density and geometrical accuracy in order to evaluate the developed L-PBF parameters and to open up possible applications.
During the Covid-19 pandemic, vocational colleges, universities of applied science and technical universities often had to cancel laboratory sessions requiring students’ attendance. These above of all are of decisive importance in order to give learners an understanding of theory through practical work.This paper is a contribution to the implementation of distance learning for laboratory work applicable for several upper secondary educational facilities. Its aim is to provide a paradigm for hybrid teaching to analyze and control a non-linear system depicted by a tank model. For this reason, we redesign a full series of laboratory sessions on the basis of various challenges. Thus, it is suitable to serve different reference levels of the European Qualifications Framework (EQF).We present problem-based learning through online platforms to compensate the lack of a laboratory learning environment. With a task deduced from their future profession, we give students the opportunity to develop own solutions in self-defined time intervals. A requirements specification provides the framework conditions in terms of time and content for students having to deal with the challenges of the project in a self-organized manner with regard to inhomogeneous previous knowledge. If the concept of Complete Action is introduced in classes before, they will automatically apply it while executing the project.The goal is to combine students’ scientific understanding with a procedural knowledge. We suggest a series of remote laboratory sessions that combine a problem formulation from the subject area of Measurement, Control and Automation Technology with a project assignment that is common in industry by providing extracts from a requirements specification.
Motile cilia are hair-like cell extensions present in multiple organs of the body. How cilia coordinate their regular beat in multiciliated epithelia to move fluids remains insufficiently understood, particularly due to lack of rigorous quantification. We combine here experiments, novel analysis tools, and theory to address this knowledge gap. We investigate collective dynamics of cilia in the zebrafish nose, due to its conserved properties with other ciliated tissues and its superior accessibility for non-invasive imaging. We revealed that cilia are synchronized only locally and that the size of local synchronization domains increases with the viscosity of the surrounding medium. Despite the fact that synchronization is local only, we observed global patterns of traveling metachronal waves across the multiciliated epithelium. Intriguingly, these global wave direction patterns are conserved across individual fish, but different for left and right nose, unveiling a chiral asymmetry of metachronal coordination. To understand the implications of synchronization for fluid pumping, we used a computational model of a regular array of cilia. We found that local metachronal synchronization prevents steric collisions and improves fluid pumping in dense cilia carpets, but hardly affects the direction of fluid flow. In conclusion, we show that local synchronization together with tissue-scale cilia alignment are sufficient to generate metachronal wave patterns in multiciliated epithelia, which enhance their physiological function of fluid pumping.
In jeder Schulklasse in Deutschland gibt es laut Statistik einen bis zwei Young Carer. Das sind Kinder und Jugendliche, die ein Familienmitglied pflegen. Doch wegen Unverständnis und Ausgrenzung seitens ihres sozialen Umfeldes vertrauen sich Young Carer niemandem an. Es mangelt schlichtweg an öffentlichem Bewusstsein für das Phänomen.
Die Kampagne #nichtbloßjung soll das ändern. Sie zeigt einer jungen Zielgruppe, was es bedeutet, nicht bloß jung, sondern Young Carer zu sein. Dabei regt sie dazu an, ebenfalls #nichtbloßjung zu bleiben, sondern als „Young Supporter“ die Young Carer zu unterstützen. Dazu wird diverse Informationsmaterial sowie ein kostenloses Armband bereitgestellt. Die Armbandtragenden zeigen so, dass sie Young Carer unterstützen und als Ansprechpersonen zur Verfügung stehen. So lernen Young Carer, dass sie mit ihrer Situation nicht allein sind und an wen sie sich gegebenenfalls wenden können.
Bitcoin is a cryptocurrency and is considered a high-risk asset class whose price changes are difficult to predict. Current research focusses on daily price movements with a limited number of predictors. The paper at hand aims at identifying measurable indicators for Bitcoin price movements and the development of a suitable forecasting model for hourly changes. The paper provides three research contributions. First, a set of significant indicators for predicting the Bitcoin price is identified. Second, the results of a trained Long Short-term Memory (LSTM) neural network that predicts price changes on an hourly basis is presented and compared with other algorithms. Third, the results foster discussions of the applicability of neural nets for stock price predictions. In total, 47 input features for a period of over 10 months could be retrieved to train a neural net that predicts the Bitcoin price movements with an error rate of 3.52 %.