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Geometrie und Funktionen
(2024)
Im Band 2 werden die Themen aus dem "Core Curriculum" der Europäischen Gesellschaft für Ingenieurausbildung (SEFI) fortgesetzt, in dem die wesentlichen Inhalte und Ziele der Mathematikausbildung für Ingenieure berücksichtigt werden:
- Differentialrechnung,
- Integralrechnung,
- Differentialgleichungen,
- Geometrie und Trigonometrie,
- Diskrete Mathematik,
- Vektoren,
- Wahrscheinlichkeitsrechnung und Statistik.
Jedes Kapitel führt in das Thema kurz ein, die verwendeten Begriffe werden definiert. Viele einfache Abbildungen tragen zur Veranschaulichung bei. Ausformulierte Lernziele, die jeweils mit "Ich kann ..." beginnen, helfen, sich die benötigte Mathematik zu erschließen. Das Arbeiten mit Kann-Listen macht den eigenen Lernerfolg für Studierende sichtbar: einfach Abhaken! Darüber hinaus verbindet es das zu Lernende mit der Meta-Ebene des Stoffs, was für nachhaltiges Erinnern entscheidend ist. Der innovative didaktische Ansatz hat sich in der Praxis bewährt.
Jedes Kapitel bietet zusätzlich eine Vielzahl an Aufgaben und schließlich ausführlichen Lösungen. Zu jeder Aufgabe gibt es eine Zeitangabe, die den Studierenden bei der Auswahl zum Anfang hilft. Die Aufgaben selbst sind unterschiedlich, teils auf Anwendung bezogen, teils zum Rechnen, teils zur Klärung der Begrifflichkeiten.
While the topic of artificial intelligence (AI) in multinational enterprises has been receiving attention for some time, small and medium enterprises (SMEs) have recently begun to recognize the potential of this new technology. However, the focus of previous research and AI applications has therefore mostly been on large enterprises. This poses a particular issue, as the vastly different starting conditions of various company sizes, such as data availability, play a central role in the context of AI. For this reason, our systematic literature review, based on the PRISMA protocol, consolidates the state of the art of AI with an explicit focus on SMEs and highlights the perceived challenges regarding implementation in this company size. This allowed us to identify various business activities that have been scarcely considered. Simultaneously, it led to the discovery of a total of 27 different challenges perceived by SMEs in the adoption of AI. This enables SMEs to apply the identified challenges to their own AI projects in advance, preventing the oversight of any potential obstacles or risks. The lack of knowledge, costs, and inadequate infrastructure are perceived as the most common barriers to implementation, addressing social, economic, and technological aspects in particular. This illustrates the need for a wide range of support for SMEs regarding an AI introduction, which covers various subject areas, like funding and advice, and differentiates between company sizes.
Innovationen sind die stärksten Gestaltungsfaktoren für eine neue vielversprechende Zukunft, da sie die wichtigsten Treiber für Wachstum und Ertrag in unserer Wirtschaft sind. Die aktuelle Zeitenwende zeigt uns sehr deutlich, dass wir ohne Innovationen bzw. Veränderungen und Anpassungen kaum noch wettbewerbsfähig bleiben, sowohl als Nation bzw. als Gesellschaft und insbesondere als Unternehmen.
Die hohe Dynamik und Komplexität der wirtschaftlichen und sozialen Prozesse setzt neue Maßstäbe an die Innovationsstrategien von Institutionen und Unternehmen.
Neue Technologien, neue Märkte, neues Kundenverhalten und der stetige Wandel sowohl in der Arbeitswelt als auch in unserem gesellschaftlichen Umfeld, wie z.B. die Digitalisierung, zeigen uns, dass allein eine Produktinnovation als solche heute nicht mehr ausreicht. Unter den genannten Randbedingungen müssen Innovationen auch in der Gestaltung von Geschäftsprozessen und Realisierung der "Work-Life-Balance" neu erdacht bzw. überprüft werden.
Der Vorsprung innovativer Produkte im viralen Wettbewerb ist oft nur kurz. Ein ganzheitliches Innovationsmanagement hat alle Bereiche des Unternehmens einzubeziehen und führt zu neuen Geschäftsmodellen, die etablierte Geschäftspraktiken verdrängen, ebenso tauchen durch neue Technologien in immer stärkerem Maße neue Anbieter auf, die die Spielregeln in den Märkten verändern.
Der 1. Deutsche Innovations-Kongress will Impulse setzen, Best-Practice-Modelle als Vorbilder anbieten und im Austausch zwischen den Referent*innen und den Teilnehmer*innen neue Wege bzw. Perspektiven eröffnen.
Wir freuen uns auf alle Teilnehmer*innen und den Erfahrungsaustausch, um aktuelle und nachhaltige Innovations-Impulse zu setzen und neue Wege erfolgversprechende Wege zu beschreiben, womit die bereits fruchtbaren Kooperationen zwischen Wirtschaft und Wissenschaft im Großraum Osnabrück noch weiter belebt werden soll.
Aktuell tragen auch 8 Studierendengruppen des Masterstudiengangs "Entwicklung und Produktion" der Hochschule Osnabrück in der Fakultät I u. I im Rahmen des Moduls "Innovationsmanagement" in Kooperation mit Unternehmen aus der Region durch die Entwicklung neuer innovativer Produkte zum Erfolg des Kongresses bei. Die Zwischenergebnisse dazu werden in einer Poster-Ausstellung präsentiert. Die Innovationsprojekte werden unter der Leitung von Prof. Dr. Jens Schäfer durchgeführt.
The 3GPP release 16 integrates TSN functionality into 5G and standardizes various options for TSN time synchronization over 5G such as transparent mode and bridge mode. The time domains for the TSN network and the 5G network are kept separate with an option to synchronize either of the networks to the other. The TSN time synchronization over 5G is possible either by using the IEEE 1588 generalized Precision Time Protocol (gPTP) based on UDP/IP multicast or via IEEE 802.1AS based on Ethernet PDUs. The INET and Simu5G simulation frameworks, which are both based on the OMNeT++ discrete event simulator, are widely used for simulating TSN and 5G networks. The INET framework comprises the 802.1AS based time synchronization mechanism, and Simu5G provides the 5G user plane carrying IP PDUs. We modified the 802.1AS-based synchronization model of INET so that it works over UDP/IP. With that, it is possible to synchronize TSN slaves (connected to 5G UEs), across a 5G network, with a TSN master clock, present within a TSN network, that is connected to the 5G core network. Our simulation results show that 500 microseconds of synchronization accuracy can be achieved with the corrected asymmetric propagation delay of uplink and downlink between the gNodeB (gNB) and the User Equipment (UE). Furthermore, the synchronization accuracy can be improved if the delay difference between uplink and downlink is known.
Recent real-time networking developments have enabled ultra reliability, very low latency and high data rates in wired networks. Wireless networking developments have also shown that they can achieve very high data rates with consistency, but they still lack in providing ultra reliability and extremely low latency. Time Sensitive Networking (TSN) developments have brought these capabilities in Industry automation and Automotive industry too. Although TSN is standardized for wired networks for a long time, for wireless networks it will be standardized within the IEEE 802.11be standard for Wi-Fi and 3GPP Release 17 for 5G in the near future. This paper provides an overview of TSN in wired and wireless networks with the aim of comparing different simulators and presenting their offered functionality and shortcomings. These tools can be used to make oneself familiar with TSN algorithms, standards, and for the development and testing of time sensitive networks. Afterwards, the paper discusses open research questions for using TSN over wireless networks.
Water retention properties of wood fiber based growing media and their impact on irrigation strategy
(2024)
Distribution of water and air in growing media during ebb-and-flow irrigation depends on water storage properties (water retention curve) and water transport properties (hydraulic conductivity) of the materials. Growing media with their high number of coarse pores are known to exhibit strong hysteresis, i.e., differences in the water retention properties during drying and wetting cycles. To account for potential ecological disadvantages of peat, wood fibers are commonly used as substitutes for peat in growing media. However, the wood fibers generally have higher air capacities and hydraulic conductivities and lower water capacities compared to peat which may results in necessary adaptions of the irrigation strategy. Tools to optimize irrigation systems are physically based water transport models, such as HYDRUS-1D, which is commonly used to describe water transport in soils, but not often for growing media. In this study, white peat and pure wood fibers were used to describe differences in their water retention behavior. Water retention curves (drying cycles) and hydraulic conductivities were measured with standard analytical procedures. Hysteresis of the water retention curves was analytically determined based on their capillary rise properties. The results were used with a modified HYDRUS-1D model to test model quality against measured water contents during ebb-and-flow irrigation cycles and to optimize the irrigation strategy for the different materials. The results showed that the model quality was sufficiently good only if the strong hysteresis of the water retention curves was considered during the simulation process. Different strategies were tested to modify ebb-and-flow irrigation (irrigation frequency, irrigation duration and irrigation height) in that way that the water suction in the root zone was similar to that of the peat material. Simulation results showed that significant improvements could only be reached by increasing the flooding depth in ebb-and-flow systems to ensure an optimum water supply of plants in the wood fiber based growing media.
Wood fibers can contribute to replacing peat in growing media and thus help to protect peatlands. As domestic, renewable raw materials, they represent a sustainable option for this purpose. To date, however, wood fibers are usually used as a peat substitute at a maxi-mum of 30% (v/v). A main reason for this limitation is the insufficient microbial stability of wood fibers, which favors nitrogen immobilization and can thus impair nitrogen supply of plants. To address this drawback, in this study wood fibers were subjected to different thermal or thermal-hydrolytic treatments. Seedling tests with napa cabbage were conducted to determine whether treated wood fibers were free of phytotoxic substances. Mixtures with 50% (v/v) wood fiber and white peat each were used. In addition, three wood fiber varieties were evaluated in the cultivation of petunia. Two wood fiber proportions (30 and 60% v/v) and two nitrogen fertilization rates (common and increased supply) were included in each case. In the seedling trial with napa cabbage, no phytotoxic effects were detectable in any of the wood fiber variants investigated. However, when cultivating petunias, both shoot mass growth and number of flowers decreased with increasing wood fiber content. In substrates with a wood fiber content of 60% (v/v), plant development was inhibited so severely that the petunias no longer achieved marketable quality. Increased nitrogen fertilization was able to compensate for this negative effect only in few cases. This suggests that other factors than nitrogen limited plant growth in wood fiber-rich substrates. Among others, physical proper-ties such as the lower water capacity of wood fibers may be a cause. More in-depth investigations are still required in this regard.