Refine
Document Type
- Conference proceeding (1039) (remove)
Is part of the Bibliography
- yes (1039)
Institute
- Informatik (570)
- Technik (273)
- ESB Business School (163)
- Texoversum (24)
- Life Sciences (11)
- Zentrale Einrichtungen (2)
Publisher
- IEEE (222)
- Springer (145)
- Hochschule Reutlingen (112)
- Gesellschaft für Informatik e.V (57)
- Association for Computing Machinery (41)
- VDE Verlag (31)
- Association for Information Systems (30)
- SciTePress (21)
- IARIA (19)
- Elsevier (18)
- RWTH Aachen (15)
- Deutsche Gesellschaft für Computer- und Roboterassistierte Chirurgie e.V. (11)
- Hochschule Ulm (11)
- Stellenbosch University (11)
- University of Hawai'i at Manoa (10)
- Curran Associates Inc. (9)
- SPIE. The International Society for Optical Engineering (8)
- Università Politecnica delle Marche (8)
- Arbeitsgemeinschaft Simulation (ASIM) (6)
- IOP Publishing (5)
- Leibniz-Universität Hannover (5)
- University of Zagreb (5)
- European Association for the Development of Renewable Energy, Environment and Power Quality (4)
- OpenProceedings (4)
- University of Colorado (4)
- University of Hawaii at Manoa (4)
- Verlag IFZ – Hochschule Luzern (4)
- Academy of Management (3)
- Cambridge University Press (3)
- Deutsche Gesellschaft für Computer- und Roboterassistierte Chirurgie e. V. (3)
- EuroMed Press (3)
- Hometrica Consulting (3)
- Technische Universität Berlin (3)
- Technische Universität Chemnitz (3)
- Technische Universität Graz (3)
- Universität Konstanz (3)
- eceee (3)
- Academic Conferences International (2)
- American Institute of Physics (2)
- American Marketing Association (2)
- Apprimus Wissenschaftsverlag (2)
- De Gruyter (2)
- Dnipro University of Technology (2)
- Duncker & Humblot (2)
- Fraunhofer Verlag (2)
- Fraunhofer-Institut für Arbeitswirtschaft und Organisation (2)
- GMDS e.V. (2)
- HTWG Konstanz (2)
- Hochschule Furtwangen (2)
- Hochschule Nordhausen (2)
- IADIS Press (2)
- IBM Research Division (2)
- International Society for Photogrammetry and Remote Sensing (2)
- International Society for Professional Innovation Management (2)
- Landesanstalt für Umwelt Baden-Württemberg (2)
- Meta Basim Press (2)
- Shaker Verlag (2)
- Smart Home & Living Baden-Württemberg e.V. (2)
- System Dynamics Society (2)
- Technische Informationsbibliothek (2)
- Technische Universität Darmstadt (2)
- The Association for Computing Machinery, Inc. (2)
- University of São Paulo (2)
- Universität Trier (2)
- VDI Verlag (2)
- WIP (2)
- ADL Romania (1)
- AKS Verlag (1)
- AMFI (1)
- Academic Conferences International Limited (1)
- Association for Computing Machinery ACM (1)
- Athens Institute for Education and Research (1)
- Atlantis Press (1)
- Baltic Management Development Association (BMDA) (1)
- Bayerisches Zentrum für innovative Lehre (1)
- British Institute of Non-Destructive Testing (1)
- Bundesverband Kraft-Wärme-Kopplung e. V. (1)
- Bundesverband Kraft-Wärme-Kopplung e.V. (1)
- CIDR (1)
- Cadence Design Systems (1)
- Carl Hanser Verlag (1)
- Copenhagen Business School (1)
- Cornell University (1)
- Cuvillier Verlag (1)
- DGMP (1)
- DITF (1)
- Design Society (1)
- Development and Entrepreneurship Agency (1)
- Dialogum GmbH (1)
- Druckerei & Verlagshaus Mainz (1)
- ECPE European Center for Power Electronics (1)
- EMAC (1)
- EPubli (1)
- ESI ITI GmbH (1)
- ETA-Florence Renewable Energies (1)
- Ed2.0Work (1)
- Edizioni Novacultur (1)
- Elektronikpraxis, Vogel Business Media GmbH & Co. KG (1)
- Energieagentur Regio Freiburg GmbH (1)
- Eurographics Association (1)
- European Accounting Association (1)
- GRID-FTN (1)
- German Medical Science Publishing House (1)
- GfA-Press (1)
- Ghent University (1)
- Global Alliance of Marketing & Management Associations (1)
- Global Science Institute (1)
- Graduiertenakademie Pädagogische Hochschulen (1)
- Hanser (1)
- Hochschule Bonn-Rhein-Sieg (1)
- Hochschule für Technik, Wirtschaft und Kultur Leipzig (1)
- IADIS (1)
- IWCS (1)
- International Association for Development of the Information Society (1)
- International Management Development Association (IMDA) (1)
- International TRIZ Official Association (1)
- International Wire and Cable Symposium Inc. (1)
- Johannes Kepler University Linz (1)
- KTH Royal Institute of Technology (1)
- Karlsruher Institut für Technologie (1)
- Lund University (1)
- MA Akademie Verlags- und Druck-Gesellschaft mbH (1)
- MDPI (1)
- Mediengruppe Oberfranken (1)
- Messe Offenburg-Ortenau GmbH (1)
- Morressier (1)
- Newcastle University (1)
- NextMed (1)
- PeerJ Inc. (1)
- Power Sources Manufacturers Association (1)
- Pro Business (1)
- Qatar University (1)
- SATC (1)
- SISSA (1)
- Sciendo (1)
- Society for Industrial and Systems Engineering (1)
- Sächsisches Textilforschungsinstitut e.V. (1)
- Süddeutscher Verlag Veranstaltungen GmbH (1)
- Tarquin (1)
- Technical Conference Management (1)
- Technische Akademie Esslingen (1)
- The Association for Computing Machinery (1)
- The British Institute of Non-Destructive Testing (1)
- The Design Society (1)
- Universitat Politècnica de València (1)
- University of Belgrade (1)
- University of Maribor Press (1)
- University of Portsmouth (1)
- University of Waikato (1)
- University of Zagreb Faculty of Organization and Informatics (1)
- Universität Bremen (1)
- Universität Hannover (1)
- Universität des Saarlandes (1)
- Verlag Werner Hülsbusch, Fachverlag für Medientechnik und - wirtschaft (1)
- WEKA Fachmedien (1)
- ZIM-Kooperationsnetzwerk Region Neckar-Alb (1)
- fortiss GmbH (1)
- gws-netzwerk für Systemische Organisations- und Personalentwicklung e.V. (1)
- libreriauniversitaria.it.edizioni (1)
- vwh Verlag Werner Hülsbusch (1)
Menopause is the permanent cessation of menstruation occurring naturally in women's aging. The most frequent symptoms associated with menopausal phases are mucosal dryness, increased weight and body fat, and changes in sleep patterns. Oral symptoms in menopause derived from saliva flow reduction can lead to dry mouth, ulcers, and alterations of taste and swallowing patterns. However, the oral health phenotype of postmenopausal women has not been characterized. The aim of the study was to determine postmenopausal women's oral phenotype, including medical history, lifestyle, and oral assessment through artificial intelligence algorithms. We enrolled 100 postmenopausal women attending the Dental School of the University of Seville were included in the study. We collected an extensive questionnaire, including lifestyle, medication, and medical history. We used an unsupervised k-means algorithm to cluster the data following standard features for data analysis. Our results showed the main oral symptoms in our postmenopausal cohort were reduced salivary flow and periodontal disease. Relying on the classical assessment of the collected data, we might have a biased evaluation of postmenopausal women. Then, we used artificial intelligence analysis to evaluate our data obtaining the main features and providing a reduced feature defining the oral health phenotype. We found 6 clusters with similar features, including medication affecting salivation or smoking as essential features to obtain different phenotypes. Thus, we could obtain main features considering differential oral health phenotypes of postmenopausal women with an integrative approach providing new tools to assess the women in the dental clinic.
Human pose estimation (HPE) is integral to scene understanding in numerous safety-critical domains involving human-machine interaction, such as autonomous driving or semi-automated work environments. Avoiding costly mistakes is synonymous with anticipating failure in model predictions, which necessitates meta-judgments on the accuracy of the applied models. Here, we propose a straightforward human pose regression framework to examine the behavior of two established methods for simultaneous aleatoric and epistemic uncertainty estimation: maximum a-posteriori (MAP) estimation with Monte-Carlo variational inference and deep evidential regression (DER). First, we evaluate both approaches on the quality of their predicted variances and whether these truly capture the expected model error. The initial assessment indicates that both methods exhibit the overconfidence issue common in deep probabilistic models. This observation motivates our implementation of an additional recalibration step to extract reliable confidence intervals. We then take a closer look at deep evidential regression, which, to our knowledge, is applied comprehensively for the first time to the HPE problem. Experimental results indicate that DER behaves as expected in challenging and adverse conditions commonly occurring in HPE and that the predicted uncertainties match their purported aleatoric and epistemic sources. Notably, DER achieves smooth uncertainty estimates without the need for a costly sampling step, making it an attractive candidate for uncertainty estimation on resource-limited platforms.
Evaluation of a contactless accelerometer sensor system for heart rate monitoring during sleep
(2024)
The monitoring of a patient's heart rate (HR) is critical in the diagnosis of diseases. In the detection of sleep disorders, it also plays an important role. Several techniques have been proposed, including using sensors to record physiological signals that are automatically examined and analysed. This work aims to evaluate using a contactless HR monitoring system based on an accelerometer sensor during sleep. For this purpose, the oscillations caused by chest movements during heart contractions are recorded by an installation mounted under the bed mattress. The processing algorithm presented in this paper filters the signals and determines the HR. As a result, an average error of about 5 bpm has been documented, i.e., the system can be considered to be used for the forecasted domain.
The article pleads for Education for Sustainable Development (ESD) in the textile and fashion sector and shows possibilities how this can be implemented from elementary school to higher education and vocational training. It begins by highlighting the non-sustainable practices and deficits that can be found in the fashion and textile sector worldwide and explains the sustainability goals in the context of the UN Roadmap ESD for 2030. In order to raise the awareness for sustainability and implement these goals, education is needed. The article introduces the concept of ESD as a guiding principle with the core element design competence, implemented by the interdisciplinary method of Design Thinking (DT). In order to successfully teach the ESD-relevant design competence, various didactic principles are required. It can be shown that they are very similar to the principles and phases of DT. Within a research project DT and its potential for implementing ESD has been investigated in teaching-learning situations at elementary schools as well as in an interdisciplinary seminar for student teachers. These findings have been transferred to the EU project Fashion DIET, which pursues the goal of implementing ESD in the textile and fashion sector. By means of an online pilot workshop, the methods and principles of DT were presented and explained to lecturers, teachers and educators, who gave their feedback on the potential of DT as a method to implement ESD as a guiding principle in their curricula.
Artificial Intelligence (AI) in der Markenführung: Künstliche Neuronale Netze zur Markenimagemessung
(2023)
Da Künstliche Neuronale Netze die Modellierung nichtlinearer und vielschichtiger Beziehungen ermöglichen, befasst sich dieser Beitrag mit deren Einsatzmöglichkeiten für die methodisch anspruchsvolle Analyse und Messung des Markenimages. Zur Veranschaulichung des konzeptionellen Ansatzes wird am empirischen Beispiel des Sportartikelherstellers adidas ein mehrschichtiges Künstliches Neuronales Netz zwischen den Bewertungen spezifischer Markenattribute und der Gesamtbewertung der Marke erzeugt. Auf der Grundlage einer Analyse der Verbindungsgewichte des Künstliches Neuronales Netzes wird die Bedeutung verschiedener Markenattribute für die Markenbewertung gemessen, wodurch sich konkrete Implikationen für die Praxis der Markenführung ableiten lassen.
The dawn of the 21st Century has witnessed a tremendous increase in trade pacts among nations, resulting in renewed hopes for sustainable enterprise development in emerging economies worldwide. Ghana and other sub-Saharan African (SSA) countries have signed onto several North-South and South-South free trade agreements with the hope of strengthening their presence in the international trade arena, and to promote economic growth in SSA. For over two decades, however, very little has changed, and many have dashed their high hopes as enterprises continue to struggle in SSA. Not even the African Continental Free Trade Agreement (AfCFTA) could renew the hopes of sceptics. Several studies opined that enterprises in SSA could improve their domestic and international competitiveness by establishing mutually beneficial partnerships with their counterparts from the Global North and South. This study delved into the issues that affect North-South and South-South business collaborations and recommends key success factors that could help promote mutually beneficial cross-border business partnerships. The research includes both literature and empirical information on the key success factors of business partnerships between African enterprises as well as between African enterprises and firms from the Global North. We approached the study qualitatively using a phenomenological research design. Research participants included important stakeholders in Africa and Europe's international trade and sustainable enterprise development ecosystem. The study identified several challenges with the current business collaborations and recommended new ways of making such partnerships more beneficial.
Die folgende Veröffentlichung ist ein Konferenzband, der im Sommersemester 2023 stattgefundenen Studierendenkonferenz Informatics Inisde, die für die Fakultät Informatik und die Studierenden ein besonderes Ereignis ist. Mit der Veröffentlichung Ihrer Artikel in diesem Konferenzband haben die Studierende eine handfeste Publikation, die durch ein Peer-Review inhaltlich qualitätsgesichert ist.
In diesem Jahr gibt es eine neue Herausforderung: Seit dem Jahr 2022 steht ChatGPT von OpenAI zur Verfügung, das verblüffende Texte mit nachvollziehbarer Argumentation verfassen kann. Eine Nutzung des Werkzeugs für die Erstellung eines wissenschaftlichen Artikels ist denkbar und gleichzeitig schwer zu beweisen. Ein kritischer Umgang mit Technologie ist wichtiger als ein pauschales Verbot. Dennoch braucht es Regeln im Umgang mit Künstlicher Intelligenz, die einen ethisch richtigen Einsatz solcher Werkzeuge begrenzt. Umso wichtiger ist es, dass umfassender Sachverstand und kritisches Denken vermittelt wird, damit mögliche Fehler oder Plagiatsfälle entlarvt werden können.
Damit sind wir mitten im Thema: Informatik ist allgegenwärtig und in äußerst vielen Produkten in der Industrie und des täglichen Lebens vorhanden. Die vielfältigen Aufsätze dieser Konferenz zeigen das. Sehen Sie selbst, wie breit die Verfahren, Algorithmen, Methoden und Technologieanwendungen sind: Von Augmented-Reality, über Videoübertragung im Operationssaal, hin zu Standards für strukturierten Daten und Künstlicher Intelligenz zeigen die Beiträge doch, wie weit läufig die Informatik inzwischen ist. Allen gemeinsam ist eines: Die menschzentrierte Anwendung von Technologie, die in dem Master Human-centered Computing als Basis aller Veranstaltungen aufgefasst werden.
Automatic segmentation is essential for the brain tumor diagnosis, disease prognosis, and follow-up therapy of patients with gliomas. Still, accurate detection of gliomas and their sub-regions in multimodal MRI is very challenging due to the variety of scanners and imaging protocols. Over the last years, the BraTS Challenge has provided a large number of multi-institutional MRI scans as a benchmark for glioma segmentation algorithms. This paper describes our contribution to the BraTS 2022 Continuous Evaluation challenge. We propose a new ensemble of multiple deep learning frameworks namely, DeepSeg, nnU-Net, and DeepSCAN for automatic glioma boundaries detection in pre-operative MRI. It is worth noting that our ensemble models took first place in the final evaluation on the BraTS testing dataset with Dice scores of 0.9294, 0.8788, and 0.8803, and Hausdorf distance of 5.23, 13.54, and 12.05, for the whole tumor, tumor core, and enhancing tumor, respectively. Furthermore, the proposed ensemble method ranked first in the final ranking on another unseen test dataset, namely Sub-Saharan Africa dataset, achieving mean Dice scores of 0.9737, 0.9593, and 0.9022, and HD95 of 2.66, 1.72, 3.32 for the whole tumor, tumor core, and enhancing tumor, respectively.
AI-based prediction and recommender systems are widely used in various industry sectors. However, general acceptance of AI-enabled systems is still widely uninvestigated. Therefore, firstly we conducted a survey with 559 respondents. Findings suggested that AI-enabled systems should be fair, transparent, consider personality traits and perform tasks efficiently. Secondly, we developed a system for the Facial Beauty Prediction (FBP) benchmark that automatically evaluates facial attractiveness. As our previous experiments have proven, these results are usually highly correlated with human ratings. Consequently they also reflect human bias in annotations. An upcoming challenge for scientists is to provide training data and AI algorithms that can withstand distorted information. In this work, we introduce AntiDiscriminationNet (ADN), a superior attractiveness prediction network. We propose a new method to generate an unbiased convolutional neural network (CNN) to improve the fairn ess of machine learning in facial dataset. To train unbiased networks we generate synthetic images and weight training data for anti-discrimination assessments towards different ethnicities. Additionally, we introduce an approach with entropy penalty terms to reduce the bias of our CNN. Our research provides insights in how to train and build fair machine learning models for facial image analysis by minimising implicit biases. Our AntiDiscriminationNet finally outperforms all competitors in the FBP benchmark by achieving a Pearson correlation coefficient of PCC = 0.9601.
Digital twins deployed in production are important in practice and interesting for research. Currently, mostly structured data coming from e.g., sensors and timestamps of related stations, are integrated into Digital Twins. However, semi- and unstructured data are also important to display the current status of a digital twin (e.g., of a machinery or produced good). Process Mining and Text Mining in combination can be used to support the use of log file data to understand the current state of the process as well as highlight issues. Therefore, issue related reactions can be taken more quickly, targeted and cost oriented. Applying a design science research approach; here a prototype as an artefact based on derived requirements is developed. This prototype helps to understand and to clarify the possibilities of Process Mining and Text Mining based on log data for production related Digital Twins. Contributions for practice and research are described. Furthermore, limitations of the research and future opportunities are pointed out.