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The association between system-justifying ideologies and attitudes toward the social market economy in Germany
Get PDFAlthough the legitimacy of an economic system is often dependent on citizen support, psychological research has paid little attention to attitudes toward economic systems. In the present study, we examined the link between two system-justifying ideologies, namely, right-wing authoritarianism (RWA) and social dominance orientation (SDO), and attitudes toward the social market economy in Germany. Drawing on system justification theory, we hypothesized that RWA would be positively and SDO negatively associated with support for the social market economy because the social component of the German economic system conflicts with beliefs inherent in SDO favoring a group-based hierarchy. Based on a quota sample of German adults ( N = 886), we found support for the predicted associations of both system-justifying ideologies with economic system support, except that RWA was negatively associated with support for the welfare component of the social market economy. However, the positive relationship of RWA with support for the social market economy only emerged after SDO was statistically controlled, suggesting a suppressor situation. These findings demonstrate that system-justifying ideologies bear different relations to pro-market attitudes depending on the type of economic regime. Implications for system justification theory are discussed
Overcoming Challenges in the Commercialization of Biopolymers : From Research to Applications—A Review
No full textBiopolymers are promising sustainable alternatives to petrochemical polymers, but the recent increase in published research articles has not translated into marketable products. Here, we discuss barriers to market entry by exploring application-specific, ecological, and economic aspects, such as the utilization of biodegradable polymers to mitigate the accumulation of microplastics. We summarize previous studies revealing how fiber surface properties and the dwell time during fiber spinning affect degradability. We show how biopolymers can be processed on existing machines and how degradability can be tailored by changing process parameters. This novel approach, known as degradation by design, will allow us to rethink product development and ensure that biopolymers are not only able to replace petrochemical polymers but also reduce the environmental harm they cause
Correction to: Viability of Flax Fiber-Reinforced Salt Cores for Aluminum High-Pressure Die Casting in Experiment and Simulation
No full textFatigue behaviour of automatically HFMI-treated welds
No full textDue to notches, welds are most critical regarding fatigue failure within cyclic loaded constructions. Therefore, various post-weld-treatment techniques like post-weld treatment by high-frequency mechanical impact (HFMI) treatment have been invented to improve the fatigue strength of welded details. The benefit, resulting from HFMI treatment, has already been proven by numerous studies. Since a manual HFMI treatment must be performed by a skilled and trained person to ensure an acceptable treatment quality, an automated application of HFMI treatment is supposed to result in a more reliable and consistent treatment result, which does not depend on the operator. Furthermore, a robotic application of HFMI treatment enables an economic implementation of HFMI treatment of automated welded constructions like offshore wind energy converters and various mechanical components, as these parts do not have to be taken out of the production chain to manually perform HFMI treatment. This paper focuses on the experimental investigation of the fatigue behaviour of automated HFMI-treated welds, using a developed robotic application of the HiFIT device (specific HFMI tool)
Sequence effects on the life estimation of welded tubular structures made of S355J2H under uniaxial fatigue loading
No full textThe use of hollow sections to form lightweight structures is widespread in common steel processing industries such as crane, commercial vehicle, steel bridge and agricultural machinery construction. The hollow sections are mainly designed as truss or frame structures, in some cases using high-strength and higher-strength steels in order to achieve optimum utilization of the component and material. A new collection of fatigue life data covering sequence effects and the accuracy of the linear damage accumulation is presented. Effects of the shape of the applied load spectra and sequence effects of different amplitudes have been investigated. This document covers tubes of 4 to 8 mm thickness made by low-carbon or mild steel S355J2H. In general, it was found that the spectrum shape and the loading sequence have an influence on the service life. Depending on the shape of the spectrum, random tests tended to lead to shorter service lives than tests with block-loading sequences. An influence of overloads was also found for the tests with interspersed overloads. Typical maximum linear damage sums taken from recommendations and codes of 0.2 or sometimes 0.5 are exceeded for all spectra investigated and in some of the cases even significantly above 1.0. Transferability of the recommendations to component-type structures like tubular joints needs revision to lift its lightweight potential. Using stress concentration factors (SCF) from finite element analysis, typical strength values for the structural and effective notch stress concepts are checked. All joints investigated show a significantly higher strength compared to the IIW recommendations using the structural stress approach or compared to the DVS 0905 with the effective notch stress approach
Intelligent algorithm selection for efficient update predictions in social media feeds
No full textEfficiently synchronizing data with social media feeds while minimizing unnecessary requests presents a significant challenge in various fields. This paper investigates prediction algorithms for determining the optimal update intervals for Facebook and Twitter (now X) feeds, focusing on metrics such as delay (the time between a post’s publication and its retrieval) and requests per post. Variations in update intervals result in different algorithms producing varying results, making the selection of the most suitable algorithm for each feed crucial yet time-intensive. To address this, we propose three strategies for algorithm selection: baseline (applying a single algorithm to all feeds), optimum (identifying the best algorithm for each individual feed), and classification (selecting algorithms through a classification process based on each feed’s unique update patterns and context). Our strategies leverage various prediction algorithms, including static and adaptive algorithms, and inhomogeneous Poisson processes. We evaluate these strategies using real-world data from Facebook and Twitter, thoroughly assessing their performance in terms of delay and request efficiency. The findings demonstrate that the strategy Optimum effectively identifies the best algorithms for each feed, ensuring the highest prediction quality, though at a considerable computational cost. On the other hand, the strategy Classification offers superior runtime performance required to select algorithms. This research highlights the trade-offs between delay and request efficiency and presents a comprehensive solution for optimizing update predictions in social media feeds
Relation between edge stress, bending strength, surface stress and fracture pattern of thermally toughened glass
No full textThermally toughened safety glass must meet safety requirements in the building industry. Here, destructive tests are defined in the product standards, which must be carried out on small, standardized format (360 mm × 1100 mm) glass elements to determine the fracture pattern and bending strength. This is costly and not in the interests of sustainability. As part of the quality control of optical anisotropy effects in thermally toughened glass, isochromatic scans that can provide information on the edge stress are acquired. The evaluation of the isochromatics and retardations at the edge with deduction of the edge stress and transfer to bending strength and fracture pattern could provide essential findings for assuring the safety requirements of thermally toughened glass. In this experimental investigation, the surface and edge stress were measured on standardized format thermally toughened safety glass, with different edge processing and glass thicknesses from three different suppliers. Afterwards, the fracture pattern is controlled, or the bending strength is analyzed in a destructive four-point bending test. Conclusively, the results from the photoelastic and destructive tests are compared to determine whether the photoelastic measurement methods used to measure surface and edge stress can be employed as quality control
Development of a model for the use of AI software in advertising by example of a trailer
Get PDFDiese wissenschaftliche Arbeit widmet sich der Anwendung Künstlicher Intelligenz (KI) innerhalb der Produktion von Werbetrailern und den daraus resultierenden Auswirkungen auf bestehende Arbeitsprozesse. Hierfür wurde ein Modell für den Einsatz von KI-Software im Werbebereich am Beispiel eines (Fernseh-)Trailers entwickelt. Nach dem Unterteilen eines Trailers in einzelne Komponenten wurden mehrere KI-Software-Tools identifiziert, um die jeweili-gen Komponenten künstlich zu generieren. Für die Einordnung der Funktionsweisen und des Potenzials der jeweiligen KI-Software wurden die Grundlagen Künstlicher Intelligenz (Machine Learning, Deep Learning bis hin zu Bild- und Tonerkennung sowie Text- Bild- und Tongenerierung) erfasst und wirtschaftliche Aspekte des Einsatzes von KI ergänzt. Anschließend wurde ein potenzielles Modell für den Einsatz von Künstlicher Intelligenz in der Trailer-Produktion entwickelt und ausgiebig getestet. Neben einer kritischen Auseinandersetzung mit der Einführung eines solchen Modells in der Wirtschaft wurden auch mögliche Probleme während der Testphase identifiziert. Anschließend wurden mithilfe von Künstlicher Intelligenz vier fertige Trailer generiert. Diese wurden dann in einer Umfrage von Branchenexperten evaluiert. Die Ergebnisse zeigen, dass die Entwicklung eines Modells für den Einsatz von KI-Software im Werbebereich sinnvoll ist. Eine Kosten- und Zeitanalyse bestätigten zudem die Rentabilität, die eine Implementierung eines solchen Modells im Vergleich zu herkömmlichen Produktions-Prozessen mit sich bringen könnte. Ein einsatzfähiges Arbeitsmodell, eine Zusammenfassung aller gewonnen Erkenntnisse sowie ein Ausblick in die Zukunft des Einsatzes von KI-Software im Werbebereich, schließen die Arbeit ab.The present study shows if and how artificial intelligence (AI) can be applied to the existing processes of producing an advertising trailer. The objective is to create a model that demonstrates how AI software can be utilized in the advertising industry, specifically in the context of movie trailers. The study begins by dissecting the trailer into various components and identifying several AI tools that can artificially generate these components. Furthermore, to gain a better understanding of the capabilities of each AI software, an overview of the fundaments of artificial intelligence, such as machine learning, deep learning, image and sound recognition as well as text, image and sound generation, is provided. Subsequently, a model for implementing artificial intelligence in trailer production is thoroughly tested and refined. Additionally, potential challenges that may arise when introducing a new system into the economy are analyzed. To assess the effectiveness of the model, four final trailers were generated or assisted by AI and then evaluated by industry experts through a comprehensive survey. The results indicate that developing a model for the use of AI software in advertising is indeed advantageous. Furthermore, a cost- and timeanalysis was conducted, confirming the potential profitability associated with implementing this model compared to traditional trailer productions methods. Finally, the study concludes by presenting an operational working model, summarizing the acquired knowledge, and providing an outlook on the future utilization of AI in the advertising sector
Trendstudie Jugend in Deutschland 2024 : Verantwortung für die Zukunft? Ja, aber
No full textThemen:
- Leben & Arbeit, Gesundheit & Nachhaltigkeit, Politik & Digitales
- Ergebnisanalyse, Interpretation und Trendauswertung zu jedem Thema
- Grundlage für Zielgruppen-spezifische Strategien
- Repräsentativität für 14- bis 29-Jährige in Deutschland
- Ansprechende und intuitive Aufbereitung mit 41 Infografiken und vielen O-Tönen
Zwei Bonus-Module:
- Lebenssituationen (Schule, Ausbildung, Studium, Erwerbstätigkeit, Arbeitslosigkeit)
- Parteipräferenzen (von AfD bis SPD)
(Quelle: https://www.digistore24.com/product/542007, abgerufen am 27.05.2024
Einsatz, Nutzen und Grenzen von ChatGPT und anderen Large Language Modellen an den bayerischen HAWs
Get PDFDie Studie analysiert Einsatz, Nutzen und Grenzen von ChatGPT und Large Language Modellen (LLMs) in der Lehre an bayerischen Hochschulen für angewandte Wissenschaften (HAWs). Sie basiert auf einer schriftlichen Onlinebefragung und leitfadengestützten Interviews unter Lehrenden, Studierenden und Funktionsträgerinnen und -träger. Insgesamt nahmen 1570 Personen an der Onlineumfrage teil und es wurden 27 Interviews geführt. Zwar variieren die Ergebnisse je nach Befragtengruppe, aber tendenziell lassen sich folgende Einschätzungen auf Basis der empirischen Daten treffen:
→ Die meisten Teilnehmenden haben ein geringes Verständnis der Nutzbarkeit von LLMs und deren technologischer Funktionsweise. Die Nutzbarkeit von Open Source LLMs oder domänenspezifisch trainierten LLMs für das eigene Fachgebiet kennt der Großteil der Teilnehmenden (überhaupt) nicht oder nur teilweise.
→ Die Einsatzhäufigkeit von ChatGPT bzw. LLMs in Lehre, Studium und Arbeitsalltag ist noch gering, vor allem wegen fehlender sinnvoller Einsatzmöglichkeiten, mangelnder Qualität der Ergebnisse und rechtlicher Bedenken. Die ChatGPT-Plusversion wird von den meisten Teilnehmenden nie genutzt.
→ Die wahrgenommene Nützlichkeit der Einsatzszenarien von ChatGPT variiert je nach ChatGPT-Version und Zielgruppe, wobei das Zusammenfassen und die Verbesserung von Texten als nützlich eingeschätzt werden.
→ Ein Verbot von ChatGPT wird überwiegend abgelehnt. Stattdessen besteht seitens der Lehrenden und Studierenden der Wunsch nach vermehrter Aufklärung über die Chancen und Grenzen von ChatGPT und Co. Zudem erhoffen sie sich finanzielle, technische und didaktische Unterstützung durch die Hochschulen.
→ Die Teilnehmenden sehen ChatGPT als eine Chance zur Verbesserung der Lehre, aber auch als eine Herausforderung für die Prüfungskultur, die rechtliche Sicherheit und die Kompetenzentwicklung.
• In Bezug auf zukünftig notwendige Kompetenzen wird angemerkt, dass es zu einem Kompetenzverlust bei den Studierenden als Konsequenz der ChatGPT-Nutzung kommen kann.
• Die Frage nach der rechtlichen Sicherheit bezieht sich nicht nur auf mögliche Datenschutz- oder Copyrightverletzungen, sondern auch auf das Prüfungswesen.
• Die Art und Weise von Prüfungen wird sich ändern (müssen), wobei mehrere Optionen thematisiert werden: von der Kennzeichnungspflicht bei der Nutzung von ChatGPT und Co. über den Wegfall reiner Wissensabfragen in Prüfungen bis hin zu den Ideen, keine theoretischen Bachelorarbeiten mehr zu vergeben und vermehrt mündliche Prüfungen einzusetzen.
Die Studie schließt mit einer Diskussion über die Rolle und Tragweite der generativen KI in der Hochschullehre und gibt Hinweise auf Materialien für die Gestaltung von innovativen und verantwortungsvollen Lernszenarien.The study analyses use, benefits, and limitations of ChatGPT and Large Language Models (LLMs) in teaching at Bavarian universities of applied sciences. It is based on a written online survey and guideline-based interviews with teachers, students, and functionaries. A total of 1,570 individuals participated in the online survey, and 27 interviews were conducted. Although results vary depending on the respondent group, the following general trends can be established on empirical data:
→ Most participants only have limited understanding of the usability of ChatGPT or LLMs and the underlying technology. The majority of participants is not (at all) or only partially familiar with open-source LLMs and LLMs specifically trained for their field.
→ The usage frequency of ChatGPT or LLMs in teaching, studying and daily professional life is still low, mainly due to the lack of meaningful application possibilities, the poor quality of results, and legal concerns. The ChatGPT Plus version is hardly used at all.
→ The perceived usefulness of application scenarios varies by version and target group, with text summarization and text improvement being rated as useful.
→ A ban on ChatGPT is predominantly rejected. Instead, teachers and students want more information about the opportunities and limitations of ChatGPT and similar tools. They are also hoping for financial, technical and didactic support from universities.
→ The participants see ChatGPT as an opportunity to improve teaching, but also as a challenge for examination practices, legality, and competency development.
• Concerning competencies required in the future, it is noted that the use of ChatGPT may lead to a loss of competencies among students.
• The question of legality not only encompasses data protection or copyright violations, but also examination practices.
• The way examinations are conducted will (have to) change, with several options being discussed: from mandatory labelling when ChatGPT and similar tools are used to the elimination of knowledge tests to the idea of no longer assigning theoretical Bachelor‘s theses and increasing the use of oral exams.
The study concludes with a discussion of the role and scope of generative AI in higher education teaching and provides insights on materials for designing innovative and responsible learning scenarios