Das Thema Künstliche Intelligenz (KI) findet auch im Kulturmarketing immer mehr Anwendung und bietet dabei vielfältige Optimierungsmöglichkeiten. Welche Chancen und Herausforderungen damit für die operativen Aufgaben, Prozesse und notwendigen Kompetenzen im Kulturmarketing einhergehen, erklärt uns Andreas Wagener, Professor für E-Commerce und Social Media an der Hochschule Hof.

Im Zuge der Covid-Pandemie hat sich insbesondere in China der Trend des “live-eCommerce“ verstärkt, der dort im Jahr 2022 auf ein Volumen von 43,2 Milliarden Yuan geschätzt wird (etwa €6Mrd.) Dieser lässt sich in etwa als „digitales Teleshopping“ umschreiben und umfasst oft eine intensive Interaktion mit dem Publikum. Zuschauer können „live“ Fragen zu präsentierten Produkten stellen. Grundsätzlich lässt sich dies auch in den virtuellen Welten realisieren, wie zum Beispiel der chinesische Handelsriese AliBaba mit seinem Ansatz auf der Plattform TaoBao zeigt. Dort entstehen eigene dreidimensionale virtuelle Shopping-Umgebungen, die per Avatar besuchbar und „erlebbar“ sind. Die einzelnen Verkaufsabteilungen und Geschäfte sind mit – virtualisierten – Mitarbeitern besetzt, welche die Kunden in „Echtzeit“ beraten. Zu festen Terminen sollen zudem – analog zu dem bereits praktizierten „gewöhnlichen“ online-Live-Shopping – interaktive Verkaufsveranstaltungen und Produktpräsentation stattfinden.

Contact Tracing Apps (CTAs) have been developed to contain the coronavirus disease 19 ( COVID-19) spread. By design, such apps invade their users’ privacy by recording data about their health, contacts, and—partially—location. Many CTAs frequently broadcast pseudorandom numbers via Bluetooth to detect contacts. These numbers are changed regularly to prevent individual smartphones from being tracked trivially. However, we find that this technology
is vulnerable to fingerprinting techniques. We measured real smartphones and observed that the Corona-Warn-App (CWA ) exhibits a device-specific latency between two subsequent broadcasts. These timing differences provide a potential attack vector for fingerprinting smartphones by passively recording Bluetooth messages. This could conceivably lead to the tracking of users’ trajectories and, ultimately, the re-identification of users.

The textile and clothing (T&C) industry is not usually viewed as an exemplar of sustainable development and the circular economy (CE), as the industry has hitherto developed its products in a linear fashion, with relatively little recycling of the finished goods. This article examines the industry’s approach to the core sustainability concept and the CE in particular through a review of the available academic literature, evidence from corporate sustainability reports and websites, and feedback from an online survey of industry professionals. More specifically, the article investigates how German T&C companies are addressing sustainability in their corporate strategies and what activities relating to the CE are being pursued in the industry. The role of digital technologies in the transition to sustainability and the CE in the German T&C industry is also explored. The study finds that whilst sustainability is now firmly embedded at the strategic level in the vast majority of the companies studied, attitudes towards the CE are mixed. The use of digital technologies in support of sustainability objectives is also limited at present, but the need to meet compliance requirements and new customer perceptions of sustainability will speed the transition to CE activities, which will be facilitated by the greater exploitation of these technologies. An operational framework for initiating such a transition is developed, and action lists in the key areas of change organization, products, and processes are presented. These may be used as a guideline for practitioners, and the findings also make a small contribution to the scarcity of literature in this field of research.

The memory controller of the CPU uses bank addressing functions to determine physical locations within DRAM DIMMs. There are many fields of application for these addressing functions, particularly in security. For exam- ple, many Rowhammer proofs-of-concept use bank addressing functions to select addresses located on the same bank but in different rows to produce row conflicts. AMD provides these addressing functions for older CPU models. Hence, research on reverse-engineering addressing functions mainly targeted Intel CPUs since Intel did not publish these functions. However, AMD stopped to publish the DRAM addressing functions several years ago. AMD manufactures roughly a third of the sold CPUs in today’s CPU market. We analyze reverse- engineering tools for addressing functions and find that they do not work with AMD CPUs, hindering reverse-engineering at- tempts and Rowhammer attacks on systems with AMD CPUs. In this paper, we introduce an approach to reverse-engineer the addressing functions of AMD CPUs, which facilitates future Rowhammer experiments on AMD CPUs.

Large language models (LLMs) have garnered significant attention, but the definition of "large" lacks clarity. This paper focuses on medium-sized lan-guage models (MLMs), defined as having at least six billion parameters but less than 100 billion. The study evaluates MLMs regarding zero-shot genera-tive question answering, which requires models to provide elaborate answers without external document retrieval. The paper introduces an own test da-taset and presents results from human evaluation. Results show that combin-ing the best answers from different MLMs yielded an overall correct answer rate of 82.7% which is better than the 60.9% of ChatGPT. The best MLM achieved 46.4% and has 7B parameters, which highlights the importance of using appropriate training data for fine-tuning rather than solely relying on the number of parameters. More fine-grained feedback should be used to further improve the quality of answers.

Background

Most migraine patients need an effective acute medication. Real-world data can provide important information on the performance of acute migraine medication in clinical practice.
Methods
We used data from the German Migraine and Headache Society Headache Registry, where patients rate efficacy and tolerability of and satisfaction with each of their acute headache medications.
Results
A total of 1756 adult migraine patients (females: 85%, age: 39.5 ± 12.8 years, headache days per month: 13.5 ± 8.1) were included. Of these, 93% used acute medication, most frequently triptans (59.3%) and/or non-opioid analgesics (56.4%), and 58.5% rated efficacy as good or very good. This was more frequent for triptans (75.4%) than for non-opioid analgesics (43.6%, p < 0.001). Among non-opioid analgesics, naproxen was rated most effective (61.9% very good or good, p < 0.001 compared to ibuprofen, acetylsalicylic acid and paracetamol). Patient-rated efficacy significantly declined with higher headache frequencies (p < 0.001), and this effect remained significant after omitting patients overusing acute medication.
Conclusion
In the present population recruited at specialized headache centers, patients rated triptans as more effective than non-opioid analgesics, naproxen as more effective than ibuprofen, and acute medication efficacy decreased with increasing headache frequency.

Trial registration: The German Migraine and Headache Society Headache Registry is registered with the German Clinical Trials Register (DRKS 00021081).

Makerspaces democratize technology access and therefore improve the chances for innovation and entrepreneurship. Nevertheless, we know little about how innovation happens in collaborative innovation spaces like makerspaces. To unleash the full potential of makerspaces, it is essential to understand what resources and environments support innovation for makerspace users. Against this background, this research study aims to explore how different makerspace user groups leverage makerspace resources during their innovation process. To achieve this, we use the resource-based view in combination with an open innovation perspective and examine the relevance of makerspace resources (knowledge, technology, social, and financial) during the different stages of the innovation journey (ideation, development and prototyping, commercialization and diffusion). In contrast to prior work, we focus on different makerspace user groups within an industry-specific makerspace and investigate how open innovation strategies (inbound, outbound, and coupled) are used to leverage the makerspace resources to develop innovation projects. Since the object of investigation is broadly unexplored and complex, we use an embedded single case study approach to explore 10 different projects within a makerspace with a specific focus on photonics. Photonics is described as a so-called enabling technology that carries a considerable potential for cross-industry innovation. The qualitative content analysis revealed that professional and hobby users differ in their makerspace resource use and their modes of openness across the innovation journey. Furthermore, we find that makerspaces can take the role of a facilitator or incubator depending on who uses the makerspace to innovate.