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Auflistung nach Autor:in "Beigl, Michael"

1 - 9 von 9
  • Textdokument
    Betriebssysteme und Rechnerverbund
    (40 Jahre Informatik an der Technischen Universität Braunschweig 1972 - 2012, 2012) Stiege, Günter; Langendörfer, Horst; Kruse, Rudolf; Zitterbart, Martina; Fischer, Stefan; Wolf, Lars; Beigl, Michael; Kapitza, Rüdiger
  • Konferenzbeitrag
    Big Data-Zentren - Vorstellung und Panel
    (Datenbanksysteme für Business, Technologie und Web (BTW 2015), 2015) Markl, Volker; Rahm, Erhard; Lehner, Wolfgang; Beigl, Michael; Seidl, Thomas
    Zur Erforschung der verschiedenen Facetten von Big Data“ wurden jüngst drei Zen- ” tren gegründet. Hierbei handelt es sich um die vom Bundesministerium für Bildung und Forschung (BMBF) geförderten Kompetenzzentren BBDC (Berlin Big Data Center, Leitung TU Berlin) und ScaDS (Competence Center for Scalable Data Services and Solutions, Leitung TU Dresden und Uni Leipzig) sowie das in Zusammenarbeit von Industrie und Forschung eingerichtete SDIL (Smart Data Innovation Lab, Leitung KIT). Diese drei Zentren werden zunächst in Kurzvorträgen vorgestellt. Eine sich anschließende Panel- Diskussion arbeitet Gemeinsamkeiten, spezifische Ansprüche und Kooperationsmöglichkeiten heraus.
  • Konferenzbeitrag
    Ensuring a Robust Multimodal Conversational User Interface During Maintenance Work
    (Mensch und Computer 2021 - Tagungsband, 2021) Fleiner, Christian; Riedel, Till; Beigl, Michael; Ruoff, Marcel
    It has been shown that the provision of a conversational user interface proves beneficial in many domains. But, there are still many challenges when applied in production areas, e.g. as part of a virtual assistant to support workers in knowledge-intensive maintenance work. Regarding input modalities, touchscreens are failure-prone in wet environments and the quality of voice recognition is negatively affected by ambient noise. Augmenting a symmetric textand voice-based user interface with gestural input poses a good solution to provide both efficiency and a robust communication. This paper contributes to this research area by providing results on the application of appropriate head and one-hand gestures during maintenance work. We conducted an elicitation study with 20 participants and present a gesture set as its outcome. To facilitate the gesture development and integration for application designers, a classification model for head gestures and one for one-hand gestures were developed. Additionally, a proof-of-concept for operators’ acceptance regarding a multimodal conversational user interface with support of gestural input during maintenance work was demonstrated. It encompasses two usability testings with 18 participants in different realistic, but controlled settings: notebook repair (SUS: 82.1) and cutter head maintenance (SUS: 82.7).
  • Zeitschriftenartikel
    Erratum zu: Praktische Anwendungen der Smart Data Analytics
    (Informatik Spektrum: Vol. 42, No. 6, 2019) Wierse, Andreas; Beigl, Michael
  • Zeitschriftenartikel
    Hybrid Adaptive Systems
    (Business & Information Systems Engineering: Vol. 66, No. 2, 2024) Benke, Ivo; Knierim, Michael; Adam, Marc; Beigl, Michael; Dorner, Verena; Ebner-Priemer, Ulrich; Herrmann, Manfred; Klarmann, Martin; Maedche, Alexander; Nafziger, Julia; Nieken, Petra; Pfeiffer, Jella; Puppe, Clemens; Putze, Felix; Scheibehenne, Benjamin; Schultz, Tanja; Weinhardt, Christof
  • Konferenzbeitrag
    Mensch-Computer-Interaktion in allgegenwärtigen Informationssystemen
    (Mensch & Computer 2001: 1. Fachübergreifende Konferenz, 2001) Beigl, Michael; Gellersen, Hans-Werner; Streitz, Norbert
    Mit der Entwicklung allgegenwärtiger Informationssysteme entstehen Alternativen zu traditionellen Formen der Mensch-Computer-Interaktion, die sich stärker am Menschen und seinen Aktivitäten orientieren. Grundlegend ist in diesem Zusammenhang die Einbettung von Computern als Sekundärartefakt in Gegenständen, Geräten und Umgebungen um diese als Mensch-Informations-Schnittstellen, bzw. für die Mensch-Mensch-Kooperation „im wirklichen Leben“ zu erschließen. Ziel dieses Workshops ist, im kleinen Teilnehmerkreis sowohl mensch-bezogene als auch technologische Fragestellungen zu diesem Thema aufzugreifen.
  • Konferenzbeitrag
    OpenEarable Suite: Open-Source Hardware to Sense 30+ Phenomena on the Ears
    (Mensch und Computer 2024 - Workshopband, 2024) Röddiger, Tobias; Knierim, Michael; Lepold, Philipp; King, Tobias; Beigl, Michael
    In this demo, we showcase the OpenEarable Suite, a comprehensive collection of ear-worn devices designed to sense and analyze over 30 different phenomena. The collection includes three distinct devices: OpenEarable 2.0, OpenEarable ExG, and OpenEarable ExG Headphones. "OpenEarable 2.0" integrates advanced sensors, such as ultrasound-capable microphones, a 9-axis inertial measurement unit, a pulse oximeter, an optical temperature sensor, and an ear canal pressure sensor, enabling extensive health monitoring, activity tracking, and human-computer interaction. "OpenEarable ExG" is an open-source platform focused on measuring biopotentials like EEG, ECG, and EMG, using up to four sensing channels, and validated for detecting eye movements, brain activity, and muscle contractions. "OpenEarable ExG Headphones" combine electrophysiological sensing with high-quality audio, utilizing OpenBCI biosignal amplification and a 3D-printed over-ear design for reliable EEG, EOG, ECG, and EMG measurements. The OpenEarable Suite aims to democratize earable research by providing accessible, open-source tools in different form factors that follow best practices in hardware and software development, facilitating diverse applications across various domains from medical to HCI.
  • Konferenzbeitrag
    PictographAI: Interactive Generation of Stylized Pictographs for Presentations
    (Mensch und Computer 2024 - Workshopband, 2024) Makarem, Sarah; Röddiger, Tobias; Riedel, Till; Beigl, Michael
    In today’s data-driven world, effective data visualization is crucial for communication. Recent studies have shown that meaningful and relevant visual embellishments and decorations can significantly enhance data visualization memorability and comprehension. Hence, we introduce PictographAI, a generative tool integrated into presentation software to transform traditional bar charts into Pictographic visualizations. Utilizing a multimodal AI pipeline, PictographAI processes text, images, and raw data from presentation slides to automatically generate contextually appropriate pictographs. Our pipeline uses an Large language model agent, a text-guided image-inpainting model, and algorithmic post-processing to make sense of the slide contents and generate pictographs. As users update their presentation slides, the AI pipeline automates the generation of new pictographs that represent the respective contents. In this work, we demonstrate the concept and working principle that motivates the system architecture and the generative AI pipeline on a bar chart generation use case that integrates into a presentation slide creation workflow.
  • Zeitschriftenartikel
    Praktische Anwendungen der Smart Data Analytics
    (Informatik Spektrum: Vol. 42, No. 6, 2019) Wierse, Andreas; Beigl, Michael