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Dualism of rationality: evidence from a new guessing game
Get PDFRationality is a widely accepted assumption in psychology and economics, but there is limited understanding of its elements. This study uses an experimental methodology, the beauty contest game, and extends it to a newly designed cheating contest game to distinguish rationality into optimality and consistency. The experiment consists of seven rounds. We include N = 52 participants. The results show that (1) human rationality is comprised of optimality and consistency, and (2) optimality is the dominant notion. In conclusion, we observe a dualism of rationality. This study provides insight into the elements of rationality and can guide future research in psychology and economic sciences
Fake-news perception vs. fake-news detection among university students A case-study on the abilities among students from Campus Heilbronn, Germany
Get PDFIn the age of viral misinformation, the ability to recognize fake news is essential, particularly for university students who primarily consume news through social media. This study examines fake news detection abilities among German students from the campus in Heilbronn, focusing on three objectives: (1) assessing detection accuracy, (2) evaluating the gap between perceived and actual ability, and (3) identifying vulnerable demographic subgroups. Based on the GermanFakeNC corpus and a literature supported questionnaire design, 55 students assessed 12 headlines and rated their confidence. The average accuracy was 66.5%, falling short of the 75% benchmark. A weak but significant correlation (r = .209, p < .001) revealed widespread overconfidence. Gender differences were evident, with male students outperforming females in both fake news detection accuracy and self-assessment. Social media usage patterns did not show any significant impact. The findings emphasize the need for evidence-based media literacy training, particularly targeting overconfidence and subgroup disparities. This contributes to better preparedness for navigating the digital information landscape
Chancen und Barrieren der Digitalisierung in der COVID-19-Krise für KMU
No full textDie digitale Transformation ist seit Jahren ein wesentlicher Treiber der Entwicklung von Geschäftsmodellen. Die COVID-19-Pandemie betrifft sowohl Organisationen als auch die Gesellschaft und macht es zwingend erforderlich, aufkommende exogene Schocks zu nutzen, um funktionsfähig und wettbewerbsfähig zu bleiben. In diesem Sinne hat COVID-19 die aufdeckende Kraft für Organisationen, sich neu zu erfinden, indem sie ihre Strategien einschließlich der entsprechenden Geschäftsmodelle neu anpassen. Zusammen mit der Notwendigkeit, physische Distanzierung zu praktizieren, wird der Ruf nach digitalen Lösungen noch kritischer. Kleine und mittlere Unternehmen (KMU) unterscheiden sich quantitativ und qualitativ von großen Konzernen. Daher können sich KMU flexibler durch disruptive Umgebungen navigieren. Sie werden oft als Rückgrat der Wirtschaft angesehen und verdienen aus diesen Gründen die Aufmerksamkeit der Forscher. Ziel unserer Studie ist es, die Potenziale der Digitalisierung für kleine und mittlere Unternehmen zu untersuchen, die besonders von exogenen Determinanten betroffen sind. Einerseits müssen die Chancen der Digitalisierung berücksichtigt werden. Andererseits sind die Herausforderungen und Einschränkungen der COVID-19-Krise besonders relevant
Alignment information via optimal transport and pre-training for neural machine translation
No full textThe demand for translation between different languages has increased rapidly as globalization has progressed. Although neural machine translation (NMT) has achieved excellent results through pre-training, existing models lack alignment information, which makes them unsuitable for specific domains. In this paper, a NMT model with alignment information via optimal transport (OT) and pre-training is proposed. First, the representation gap between different languages is narrowed by using alignment information via OT and pre-training (OTAP) to generate domain-specific data for information alignment, thereby learning richer semantic information. Second, a lightweight model, called the DR-Reformer, is introduced, which uses the Reformer as the backbone network and incorporates Dropout and Reduction layers to reduce model parameters and improve computational efficiency without sacrificing accuracy. Experiments conducted on the Chinese and English datasets of AI Challenger 2018 and WMT-17 show that our proposed algorithm outperforms existing algorithms
Towards relevant human-vehicle interaction data for perceptive machine learning
Get PDFMachine learning models, particularly those used in open-world settings like autonomous driving, require extensive and diverse datasets for effective training. However, the overabundance of standard situations in large datasets often leads to underrepresentation of rare scenarios and edge cases, which are crucial for achieving high performance across all situations. This work proposes a simulation framework for capturing human-in-the-loop simulation data, enabling the creation of realistic and diverse datasets for machine learning models as well as human behavior studies. The framework combines full body motion capture with virtual reality to record scene-relevant interactions between humans and virtual objects, allowing for the generation of various ground truths in simulation. To validate the effectiveness of this approach, an action recognition model is trained on simulated data generated by the proposed framework. From the point of view of a vehicle, the model needs to determine if the vehicle is the intended target of a waving pedestrian. The investigation into different keypoint representations and spatial encodings reveals the importance of integrating spatial and contextual data for accurate action recognition. Furthermore, the results show that human-in-the-loop simulations can effectively capture complex human behaviors and interactions, enabling the creation of more realistic and diverse datasets for machine learning models
Reskilling and upskilling in a globalized economy : essential strategies for workforce transformation
No full textThis book provides an in-depth exploration of upskilling and reskilling strategies, essential in today’s rapidly evolving and complex global landscape. The intensifying war for talent—driven by macro trends such as digitalization, AI, climate change, hybrid working, and demographic shifts—has made addressing the skills shortage a top priority for business leaders. These global challenges not only require organizations to proactively identify and integrate future skills through targeted training programs but also demand a shift toward socially just and ecologically sustainable practices.
Grounded in cutting-edge research and proven practices, this book bridges the gap between theory and practice. It is an invaluable resource for HR professionals, business leaders, and educators dedicated to building a future-ready workforce
Reflectometric-based sensor arrays for the screening of kinase-inhibitor interactions and kinetic determination
Get PDFKinases are involved in numerous cellular processes but possibly also in tumor progression. Several kinase inhibitors are approved as drugs and there is an intense search for new inhibitors in pharmaceutical research. In this study, we present a new analytical method based on reflectometric interference spectroscopy, RIfS, for kinase and inhibitor screening. First, the sensor surface was optimized to reduce non-specific binding. Different inhibitors, e.g. staurosporine or fasudil, were immobilized on the transducer surface. Different kinases (focal adhesion kinase and cAMP-dependent protein kinase) were flushed over the sensor with the immobilized inhibitors. The specific interaction was proven by binding inhibition assays. The kinase-inhibitor interaction was monitored label-free and recorded in real time allowing the binding curves to be used to determine the association and dissociation rate constants as well as the affinity. These constants differed depending on the specific kinase-inhibitor pair, which was well expected from parallel docking simulations and measurements with microscale thermophoresis. The strategy was successfully transferred to 1-lambda reflectometry, a modification of RIfS, to enable the simultaneous monitoring of several kinase-inhibitor interactions in 5×7 small spots increasing throughput and automation on a sensor array with imaging detection. Importantly, the techniques developed here can provide both kinetic and thermodynamic data for a multitude of kinases in a single screening approach, which allows for both protein kinase and inhibitor screening
You don't just use software processes, you have to engineer them: a teachers' experience report
Get PDFSoftware processes are the game plan to develop comprehensive software systems, and there are many ways to teach software processes. Nowadays, the normal approach is to teach students to use software processes correctly, usually by explaining what agile methods are about or by introducing tools that already implement selected processes, and then letting students apply such selected tools and methods in smaller projects or project courses. However, while this approach addresses the application of, e.g., Scrum or Unit Testing, the question of how a company develops its own software process is not answered. With this paper, we address this issue and share our experiences from more than 15 years of teaching the analysis, design, realization, and improvement of software processes in our joint Software Process Engineering course, which is based on a structured Software Process Improvement model. We contribute insights into the process improvement model that builds the foundation of the course, an overview of the course content, and we share our experiences, lessons learned, and recommendations for teachers
Mit digitalen Technologien zur nachhaltigen Wertschöpfung
Get PDFZur Erreichung der geforderten Klimaneutralität kommt dem Industriesektor als einer der fünf emissionsintensivsten Sektoren eine große Bedeutung zu. Die zentrale Aufgabe ist es, Wirtschaftlichkeit und Ressourcenminimierung zu vereinen und Fabriken zum Ort nachhaltiger Wertschöpfung zu entwickeln. Zugleich fördern moderne Technologien die Entwicklung neuer Produkte und innovativer Geschäftsmodelle, wodurch Fabriken an wandelnde Anforderungen anpassbar gestaltet werden müssen. Zukünftig wird sich dieser Trend intensivieren und folglich die Themen der industriellen Agenda bestimmen. Bereits heute strukturieren führende Produktionsunternehmen ihre Wertschöpfungsnetzwerke daher aus einer ganzheitlichen Betrachtungsweise heraus: Das Supply Chain Management, die Fabrikplanung sowie die Produktionsplanung und -steuerung (PPS) werden dabei nicht als isolierte Disziplinen verstanden, sondern als eng verzahnte Elemente, die sich gegenseitig beeinflussen und verstärken sollten. Eine derart integrierte Optimierung der Wertschöpfungssysteme führt dabei nicht nur zum ökonomischen Vorteil, sondern ermöglicht genauso, die ökologische Bilanz signifikant zu verbessern
The desire to know: Gen Z's transparency requirements in fashion e-commerce
No full textThis study delves into Gen Z's demands for transparency in fashion. Through in-depth interviews with Gen Z consumers, key transparency themes are identified. The findings offer valuable managerial implications for brands seeking to engage with Gen Z and provide a deeper understanding of this generation’s attitude behavior gap regarding sustainability