Offenburg University of Applied Sciences
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Energy Optimization for Companies with Digital Flex Twins
No full textIn this paper we report on further success of our work to develop a multi-method energy optimization which works with a digital twin concept. The twin concept serves to replicate production processes of different kinds of production companies, including complex energy systems and test market interactions to then use them for model predictive optimizing. The presented work finally reports about the performed flexibility assessment leading to a flexibility audit with a list of measures and the impact of energy optimizations made related to interactions with the local power grid i.e., the exchange node of the low voltage distribution grid. The analysis and continuous exploration of flexibilities as well as the exchange with energy markets require a “guide” leading to continuous optimization with a further tool like the Flexibility Survey and Control Panel helping decision-making processes on the day-ahead horizon for real production plants or the investment planning to improve machinery, staff schedules and production
infrastructure
Increasing Customer Interaction of an Online Magazine for Beauty and Fashion Articles Within a Media and Tech Company
No full textThe present paper addresses the research question: What recommendations for action and potential adjustments should an online magazine for beauty and fashion implement in order to make affiliate articles in these sections even more appealing to the target group and provide added value for them?
To be able to answer this research question, three hypotheses were defined and tested with using qualitative and quantitative research. The qualitative research consisted of user experience testings, where four affiliate articles in the fields of beauty and fashion were tested with 13 participants. The quantitative research involved collecting, analyzing and evaluating data from the four affiliate articles conducted with the company's real-life target group. Based on these results, recommendations for action were derived, which should not only improve the quality of the content in the future, but also increase the efficiency of the implementation of those articles
Verjährung einer nach “Hamburger Brauch“ vereinbarten Vertragsstrafe
No full textUrteilsanmerkung zu BGH v. 27.10.2022 - I ZR 141/2
Webcam-Aufzeichnungen eines Dritten als Beweismittel
No full textUrteilsanmerkung zu OLG Saarbrücken vom 13.10.2022 – 4 U 111/2
Modellierung der Direktreduktion von Eisenerz auf Partikelebene
No full textUm den Prozess der Direktreduktion von Eisenerz computergestützt zu simulieren, werden mathematische Modelle, zur Beschreibung von Gas-Feststoff-Reaktionen, in Python implementiert. In der vorliegenden Arbeit wird ein einzelnes Pellet aus Eisenerz, welches sich in einem Gasstrom aus reinem Wasserstoff befindet, betrachtet. Es werden mehrere Modellansätze aus der Literatur miteinander verglichen und davon geeignete zur recheneffizienten Implementierung ausgewählt. Die entwickelte Simulationssoftware besitzt eine grafische Oberfläche und bietet die Auswahl aus drei Modellen mit unterschiedlichem Detaillierungsgrad. Diese sind vollständig parametriert und die meisten Parameter werden temperaturabhängig bestimmt oder sind frei wählbar. Die Durchführung von Parameterstudien ist über die lineare Variierung eines beliebigen Parameters möglich. Die Ergebnisse der Simulation können dann in Abhängigkeit der Zeit dargestellt oder im CSV-Format exportiert werden. Die Rechenmodelle sind in einem separaten Python-Modul zusammengefasst und können einfach in eine übergeordnete Modellierung eingebaut werden. Zur Validierung erfolgt ein Abgleich mit experimentellen Literaturdaten. Abschließend werden die Stärken und Schwächen der implementierten Modelle gegenübergestellt und bewertet.For the computer-aided simulation of the direct reduction of iron ore, mathematical models to describe gas-solid reactions are implemented in Python. In this work, a single pellet of iron ore, which is surrounded by a gas stream of pure hydrogen is considered. Several modeling approaches from the literature are compared, in order to select suitable models for computing efficient implementation. Thereby analytical models are solved via numerical methods. The simulation software is developed in combination with a graphical user interface and provides three simulation models. Important parameters are calculated depending on temperature, but all of them can also be tweaked manually. To conduct a parameter study, the chosen parameter can be varied in linear steps. The results of the simulation can be plotted over time or exported to a CSV-format. The calculation models are all combined in one Python module and are easily importable by a superordinate reactor model. For validation, a comparison is made with experimental data from the literature. In conclusion, the strengths and weaknesses of the implemented models are assessed in contrast to each other
Konzeption und Aufbau eines Antriebsstrangs- und Elektromotorenprüfstands
No full textDie Arbeit beinhaltet die Konzeption und den Aufbau eines Prüfstandes für den Elektromotor sowie den Antriebsstrang des Hocheffizienzfahrzeugs "Schluckspecht S6" der Hochschule Offenburg. Neben Beschreiben des Vorgehens bei dem Entwerfen von benötigten CAD-Modellen wird auch auf die Auswahl und Implementierung elektronischer Komponenten sowie die Programmierung des verwendeten Mikrocontrollers eingegangen. Die Ergebnisse eines ersten Tests des Prüfstandes werden außerdem aufgezeigt und diskutiert
Automatic Product Identification Using Deep Learning
No full textIn the past ten years, applications of artificial neural networks have changed dramatically. outperforming earlier predictions in domains like robotics, computer vision, natural language processing, healthcare, and finance. Future research and advancements in CNN architectures, Algorithms and applications are expected to revolutionize various industries and daily life further. Our task is to find current products that resemble the given product image and description. Deep learning-based automatic product identification is a multi-step process that starts with data collection and continues with model training, deployment, and continuous improvement. The caliber and variety of the dataset, the design selected, and ongoing testing and improvement all affect the model's effectiveness. We achieved 81.47% training accuracy and 72.43% validation accuracy for our combined text and image classification model. Additionally, we have discussed the outcomes from the other dataset and numerous methods for creating an appropriate model
Kritische rechtsfokussierte Analyse internationaler Carve-Out-Transaktionen
Get PDFIm Rahmen dieser Studie sollen Struktur und der Ablauf internationaler Carve-Out-Transaktionen dargestellt werden. Der Fokus liegt hierbei auf den rechtlichen Aspekten solcher Transaktionen. Nichtsdestotrotz, da internationale Carve-Out-Transaktionen gerade eine sehr enge und komplexe Verflechtung rechtlicher, organisatorischer und strategischer Aspekte ausmacht, soll die internationale Carve-Out-Transaktion als Ganzes beleuchtet werden
Deep Diffusion Models for Multiple Removal
No full textSeismic data processing involves techniques to deal with undesired effects that occur during acquisition and pre-processing. These effects mainly comprise coherent artefacts such as multiples, non-coherent signals such as electrical noise, and loss of signal information at the receivers that leads to incomplete traces. In this work, we employ a generative solution, since it can explicitly model complex data distributions and hence, yield to a better decision-making process. In particular, we introduce diffusion models for multiple removal. To that end, we run experiments on synthetic and on real data, and we compare the deep diffusion performance with standard algorithms. We believe that our pioneer study not only demonstrates the capability of diffusion models, but also opens the door to future research to integrate generative models in seismic workflows