Process mining has emerged as a powerful technique for analyzing and improving business processes. In this research paper, the application of process mining in a vertically integrated small-scale smart factory is explored. The study aims to identify challenges, analyze data issues, and explore the potential of process mining as a tool for process optimization. Employing a case study approach, data is collected from the entire process and analyzed using process mining software. The findings show how to use data to enable process mining in current scenarios. Challenges related to data synchronization and the impact of network delays on data accuracy are revealed. However, despite the challenges identified, this research demonstrates the potential of process mining to drive process optimization in smart factory environments. This paper contributes to the field of process mining and provides valuable information for academia and industry professionals seeking to optimize production processes through data-driven analysis in the era of Industry 4.0.

The paper presents SPORE, a Spatial Recommender System. As we enter a period of unprecedented collaboration between authors and computers, where artificial intelligence in particular seems likely to act increasingly in a co-authoring capacity, SPORE offers a different approach to collaboration. More organic and exploratory than other automated or procedural systems, SPORE aims to mimic the process of storybreaking that already exists in the creative industries.

Vladimir Propp (1895–1970) was a Russian folklorist, who identified what he considered the 31 fundamental actions of major characters and their consequences for a story, actions which he called functions. This paper focuses on one specific part of this principle—spheres of action—and considers how they might be explored using SPORE and its underlying infrastructure Mother, a spatial hypertext-based recommender system developed by the authors.

Corona hat uns alle gelehrt, dass auch grundsätzlich in virtuellen Umgebungen Leben möglich scheint – sei es im Home-Office oder bei digitalen Veranstaltungen. Vermutlich ist es mehr als ein zeitlicher Zufall, dass virtuelle Shopping- und Marketing-Umgebungen gerade in dieser Zeit einen neuen Trend beschreiben. Nicht erst seit Mark Zuckerberg das „Metaverse“ ausgerufen hat, bilden sich virtuelle Welten, in denen digitale Avatare und „Digital Humans“ miteinander interagieren, in denen virtuelle, immaterielle „Sachgüter“ - virtuelle Kunst, Mode, Luxusgüter und Immobilien als „unique“ NFTs handelbar sind und die zunehmend auch für die Führung von „Offline“-Marken genutzt werden.

Der angestrebte Artikel versucht, das Marktsystem der Metaversen zu erfassen und widmet sich dabei vor allem den Chancen, die sich traditionellen Unternehmen aus der analogen oder „klassischen“ Online-Welt eröffnen: Welche Geschäftsmodelle bestehen – auch für kleinere Unternehmen und den Mittelstand? Welches sind die Erfolgsfaktoren – für den virtuellen Handel und für ein nachhaltiges Branding? Welche Hürden sind dabei zu überwinden? Und wie sehen Erfolg versprechende Konzepte aus?

Letztlich geht es im Kern um die Frage: Ist die Zukunft des Shoppings virtuell?

The project Symotiv’s (http://symotiv.de) goal is to describe the complex function of a symphony through an interactive experience of the orchestra’s digital twin. We are capturing the musicians, their instruments and their sounds with machine learning based 3D human pose estimation and visualize them in Virtual Reality in a three-dimensional, virtual concert hall. Our audience steps into the role of the conductor and experience the scene and the sound from a perspective within the orchestra. This opens the possibility of experiencing and understanding what is happening from new spatial, but above all sonic perspectives.

In this paper we are describing our preliminary studies and proto- types for evaluating a surfer’s performance on a stationary wave. We are briefly describing the sport’s environment and development and the current state-of- the-art of machine learning based single camera tracking approaches we have evaluated and applied. The main part of the paper deals with the first implemen- tation, the tracking and the results of the evaluation of the movements of two surfers. We are closing with our lessons learned and our next steps.

The aim of the project Symotiv (http://symotiv.de) is to introduce people to classical music through interaction with a virtual orchestra. With the help of Virtual Reality, it does not only enable to immerse oneself in a three-dimensional, virtual concert hall, but also to experience images and sound from the perspective of a musician. This opened the possibility of experiencing and understanding what is happening from new spatial, but above all sonic perspectives. Therefore, we developed a workflow to capture the motions and sound of 50 musicians and the conductor by using a camera-based Machine Learning approach.

The design review process - as part of the building permit - is mandatory for numerous construction projects in Germany. The paper-based review process is currently state of the art due to the obligation of documentation by law with legally binding signatures, e.g. for the construction process.

The application of BIM in the construction industry is increasing. Though the process of model sharing is specified in EN ISO 19650-4, the integration of the design review process has not been examined using BIM yet. In the review process, it is necessary to check structural analysis and other documents, too. Hence, the process of design review using various documents shall be linked to the steps proposed in ISO 19650-4.

The authors recommend a BIM-based digitalized design review process based on ISO 19650-4. lt is shown how the template for the review process can be adjusted to legal requirements for digital proceedings and can be used for the complete life cycle of a building better than the paper-based documentation.

In this work we are describing our preliminary experimental evaluation of open-source machine learning based pose estimation solutions for tracking a surfer’s skeleton on a stationary wave. We are briefly describing the sport’s environment and development and the current state-of-the-art of machine learning based single camera 2D and 3D pose estimation solutions. The main part of the paper deals with the experiment’s setup and the interpretation of the resulting data of the movements of one surfer. We are closing with our lessons learned and our next steps. 

We present ASR Bundestag, a dataset for automatic speech recognition in German, consisting of 610 hours of aligned audio-transcript pairs for supervised training as well as 1,038 hours of unlabeled audio snippets for self-
supervised learning, based on raw audio data and transcriptions from plenary sessions and committee meetings of the German parliament. In addition, we discuss utilized approaches for the automated creation of speech datasets and assess the quality of the resulting dataset based on evaluations and finetuning of a pre-trained state of the art model. We make the dataset publicly available, including all subsets.

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 encounters. These numbers are changed regularly to prevent individual smartphones from being trivially trackable. However, the effectiveness of this procedure has been little studied.

We measured real smartphones and observed that the German 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 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).