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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.
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.
Enhancing the nutritional value of pears through agronomic biofortification with iodine (Abstract)
(2024)
Artificial intelligence (AI) and human-machine interaction (HMI) are two keywords that usually do not fit embedded applications. Within the steps needed before applying AI to solve a specific task, HMI is usually missing during the AI architecture design and the training of an AI model. The human-in-the-loop concept is prevalent in all other steps of developing AI, from data analysis via data selection and cleaning to performance evaluation. During AI architecture design, HMI can immediately highlight unproductive layers of the architecture so that lightweight network architecture for embedded applications can be created easily. We show that by using this HMI, users can instantly distinguish which AI architecture should be trained and evaluated first since a high accuracy on the task could be expected. This approach reduces the resources needed for AI development by avoiding training and evaluating AI architectures with unproductive layers and leads to lightweight AI architectures. These resulting lightweight AI architectures will enable HMI while running the AI on an edge device. By enabling HMI during an AI uses inference, we will introduce the AI-in-the-loop concept that combines AI's and humans' strengths. In our AI-in-the-loop approach, the AI remains the working horse and primarily solves the task. If the AI is unsure whether its inference solves the task correctly, it asks the user to use an appropriate HMI. Consequently, AI will become available in many applications soon since HMI will make AI more reliable and explainable.
Nostalgia is a construct that, even when rooted in lived experiences, serves the ultimate purpose of creating a desired sense of world. Fundamental cognitive competencies, including memory and imagination, are utilized by the nostalgic subject to fulfill a need for narrative coherence. A temporal or spatial distance is necessary for the occurrence of a nostalgic episode, which can be conceptualized as a “had been” state of being, as direct access to the experience is often impossible. Nostalgia may thus be viewed as a tool for sense-making rather than solely as a yearning for the past. The nostalgic narrative form is a construct that permits human subjects to comprehend their existence in the world while drawing upon their roots. These tools for sense-making serve as bridges between past experiences and current conditions. Ultimately, nostalgic identity is not just about longing for the past but also about utilizing the past as a resource for navigating the labyrinths of the present. Analyses are conducted to examine the medium of music video at three levels - auditory, visual, and linguistic - in order to investigate the strategies and techniques employed by the Iranian diaspora to create nostalgic narratives. Samples of original pieces and renditions are contrasted in order to identify elements of nostalgic narrativity. Drawing on empirical research, it is argued that the unity of a music video arises from the integration of separate layers of sensory and conceptual inputs that have been composed towards an affective resonance and narrative coherence.
Methods: Systematic review of randomized controlled trials (RCT). Searches were conducted in five electronic databases. Studies were selected if they included patients with NP over 18 years old treated with aerobic exercise (AE) (e.g., cycling, running, hiking, and walking). The main outcome of interest was pain intensity. Qualitative and quantitative data were extracted. The risk of bias (RoB) was determined using the Cochrane RoB Tool-2 and the overall certainty of the evidence with the GRADE recommendations.
Results: Out of 21,585 initial records screened, a total of six individual studies published in ten manuscripts were included. There was a great heterogeneity between protocols, comparisons, and studies’ results (different magnitudes and directions). When looking at the effect of aerobic exercise versus control groups or other interventions on pain intensity measured with the VAS, not statistically (nor clinical) significant differences between aerobic exercise and control groups (MD [95%CI] 5.16 mm [-6.38, 16.70]) were identified. The combined effect of AE plus other interventions seems to be effective. Strength exercise obtained better effects than aerobic exercises (MD [95%CI]: -11.34 mm [-21.6, -1.09]).
Conclusions: Aerobic exercise presented positive results to reduce pain intensity, and improving disability, and physical and emotional functioning. However, the evidence is restricted, low quality, and heterogeneous.
Methods: The searches were conducted on five electronic databases. RCTs or CTs with patients over 18 years old of both sexes with OFP diagnoses were targeted. The intervention of interest was AE (i.e., walking, cycling, and running), compared to any other conservative and non-conservative therapy. The primary outcome was pain intensity. Risk of bias (RoB) was done with the Cochrane RoB tool (RoB 2). The overall certainty of the evidence was evaluated with GRADE.
Results: Out of 21,585 initial records found in the initial database search, only one study (reported on three manuscripts) was included. The diagnosis of interest was headache plus temporomandibular disorders (TMD). Three treatment groups (strengthening (Str) exercise + manual therapy (MT) (G1); AE + MT + Str exercises (G2); AE (G3)) were compared. The main outcome was pain; the secondary outcomes included disability, strength, anxiety, and quality of life. The combined treatment (AE+MT+Str exercises) had the strongest effect to decrease pain and headache intensity in patients with OFP (SMD: 9.99 [95%CI: 7.19, 12.80].
Conclusions: a multimodal treatment strategy achieved the greatest positive effects on pain and other outcomes in the short/medium term. AE seems to be an important component of this strategy. However, the scientific evidence supporting AE’s isolated effect is limited, indicating a research gap in this scientific field.
The excitement sparked by the emergence of AI open platforms has encountered significant scrutiny from educators and educational planners, who have raised valid concerns about issues such as plagiarism, testing protocols, and the authenticity of content submitted by students. While these concerns are timely and crucial, it's essential not to overlook other pressing issues that often go unnoticed in the lived educational experience of learners, particularly within the field of social sciences. This paper aims to advocate for a humanistic approach with a focus on education in the generative AI Era.
Einleitung
Die Prävalenz der über 80-jährigen bei Ulcus cruris venosum (VLU) beträgt 4-5 %, obwohl diese Altersgruppe nur 1 % der Gesamtbevölkerung ausmacht. Zusätzlich wird bei VLU-Patienten häufig eine Mangelernährung beobachtet. Insbesondere geriatrische Patienten leiden darunter. Dabei ist bekannt, dass Mangelernährung Einfluss auf die Wundheilung und somit auf die Lebensqualität der Patienten hat. Diverse Studien beschreiben erste erfolgreiche ernährungstherapeutische Ansätze für einen beschleunigten Wundheilungsprozess. Allerdings ist die Ernährungstherapie bei VLU-Patienten wenig erforscht. Ziel dieser Arbeit ist es einen Überblick über den ernährungsphysiologischen Einfluss zur VLU zu schaffen, um mögliche Ernährungsinterventionen für geriatrische Patienten zu erhalten.
Iron deficiency is a global issue and can lead to a variety of clinical pictures. The biofor-tification of vegetables with iron could complement the existing portfolio of iron-rich products, thus improving iron supply in the long term. In order to determine whether the iron-biofortified vegetables could meet this demand and would address appropriate target groups, a quantitative online survey was conducted in Germany. Based on 1000 consumer responses, a cluster analysis was performed. The results showed a four-cluster solution. The first cluster was holistically engaged, the second was fitness-affine but health unconcerned, the third cluster consists frugal eaters with a focus on medical prevention, and the fourth cluster are hedonists. No cluster focused its consumption on iron-enriched products, but instead all developed an individual mix of the three product groups.
Die Digitalisierung des Bodenbeprobungsverfahrens mit einer automatisierten Generierung einer Düngeempfehlung auf Grundlage der analysierten Bodennährstoffgehalte – direkt nach Beendigung der Bodenbeprobung auf dem Acker – ist ein übergeordnetes Ziel bei der Nutzung des mobilen Feldlabors „soil2data“. Neben den Bodennährstoffanalyse-Ergebnissen sind für die Umsetzung einer automatisierten generierten Düngeempfehlung weitere Informationen notwendig.
Die Quellen dieser Informationen haben einen unterschiedlichen Ursprung. Es sind Daten aus verschiedenen Quellen vom Bewirtschafter, von Dienstleistern und vom mobilen Feldlabor, welche miteinander verknüpft und synchronisiert werden müssen. Für einen automatisierten Prozessablauf zur Generierung einer Düngeempfehlung ist die Datenorganisation eine essenzielle Voraussetzung. Die Grundlage der Empfehlung sind die Tabellenwerke der offiziellen Düngeempfehlung, die bei den für die Düngung zuständigen Behörden der Bundesländer vorliegen. In dieser Publikation werden die notwendigen Daten und der Prozessdatenfluss für die Bodenbeprobung und Düngeempfehlung-Generierung beschrieben und grafisch dargestellt.
Knowledge of the maximum friction coefficient µmax between tire and road is necessary for implementing autonomous driving. As this coefficient cannot be measured via existing serial vehicle sensors, µmax estimation is a challenging field in modern automotive research. In particular, model-based approaches are applied, which are limited in the estimation accuracy by the physical vehicle model. Therefore, this paper presents a data-based µmax estimation using serial vehicle sensors. For this purpose, recurrent artificial neural networks are trained, validated, and tested based on driving maneuvers carried out with a test vehicle showing improved results compared to the model-based algorithm from previous works.
Within the consortium “Experimentation Field Agro-Nordwest”, a practical concept for knowledge and technology transfer of digital competence in agriculture was created. For this purpose, the web-based e-learning system “SensX” was set up, consisting of videos, presentations and instructions. In addition, the classical e-learning concept was extended by data sets, student experiments and sensor data of plants acquired by a remote phenotyping robot. This resulted in a massive open online course (MOOC), which was tested with agricultural and biotechnology students in higher education at the University of Applied Sciences Osnabrück over two years. The evaluation process of “SensX” included an empirical survey, qualitative interviews of the participating students by an external institution and an evaluation of the concept by the lecturers.
Computer-image processing becomes more and more important in the analysis of data in biological and agricultural research and practice. However, robust image processing is highly de pendent on the histogram analysis algorithms used and the quality of the data being processed. The algorithm presented here aims to improve the accuracy of the classification of image data generated under complex boundary situations and inconsistent lighting conditions. Using the example of the determination of nitrogen content of tomato leaves and the qualitative determination of starch con tent of apples on the basis of color image processing, we showed that the developed algorithm is able to perform a robust classification and represents an improvement to simple histogram analysis.
Fütterung von Jungpferden
(2023)
Fütterung von Zuchtstuten
(2023)