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Combining Data- and Knowledge-Driven AI with Didactics for Individualized Learning Recommendations

Landes, Dieter; Sedelmaier, Yvonne; Böck, Felix; Lehmann, Alexander; Fraas, Melanie...

Proc. 15th IEEE Global Engineering Education Conference (EDUCON 2024), Kos, Griechenland 2024.


Peer Reviewed
 

Students in higher education tend to become increasingly heterogeneous groups of learners. This is due to different levels of prior knowledge or competences, diverse
learning styles, differing affinity to (digital) media, and other factors. Learner-centred education needs to cope with that heterogeneity in order to make specific learning offers to the
individual learner. This is difficult in physical classes where the coaching effort cannot be increased without limitation. This paper presents an individualized digital learning environment, iLE, that is intended to be used as an additional learning aid that supplements physical classes. iLE provides recommendations of learning material such as learning videos targeted to the specific needs of individual learners. The paper presents the technical approach behind iLE, in particular a combination of data- and knowledge-driven artificial intelligence techniques, as well as the didactical underpinning of iLE.

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Multi-Pedestrian Tracking and Map-based Intention Estimation for Autonomous Driving Scenario

Dehghani, Ali; Patiño Studencki, Lucila (2024)

10th. International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS) 2024.


Peer Reviewed

Die neue Wärmepumpen-Generation – Teil 1: Kältemittel, Effizienz und Bauweise

Schaub, Michael (2024)

HLH 75 (05), 22-25.
DOI: 10.37544/1436-5103-2024-05-22


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Gesundheitstag für Lehrkräfte

Kohls, Niko (2024)

Organisation.



Second Workshop on AI for AI Education (AI4AILearning)

Kohlhase, Michael; Leidner, Jochen L.; Schmid, Ute; Wolter, Diedrich (2024)

held at KI 2024: 47. Deutsche Jahrestagung für Künstliche Intelligenz, Würzburg, 23.09. - 27.09.2024.


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Die neue Wärmepumpen-Generation: Propan oder R32?

Schaub, Michael (2024)

7. Internationale Fachtagung Bauphysik & Gebäudetechnik (BGT 2024), Friedrichshafen, 365-375.


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Multidimensional AI-based Health-Assistant

Blümlein, Markus; Leidner, Jochen L. (2024)

Poster, presented at Networking for Research – German Universities of Applied Sciences and Researchers from Scotland (UDIF-HAW), DFG (German Research Foundation) and SULSA (Scottish Universities Life Sciences Alliances), online, 2024-04-24.


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Analytical and Numerical Analysis of the De Haller Criterion for Low-Pressure Axial Fans

Epple, Philipp; Fritsche, Manuel (2024)

Symposium on Innovative Simulations in Turbomachinery ISimT München.



Spaces to heal: Using the psychological impact of architecture

Vollmer, Tanja C.; Koppen, Gemma (2024)

Book: Rising Oceans & Spaces that Care , 109–112.


Peer Reviewed
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Gesunde Architektur im bezahlbaren Wohnbau [Healthy architecture in affordable housing]

Koppen, Gemma; Vollmer, Tanja C.; Hesselschwerdt, Pia (2024)

DW Die Wohnungswirtschaft (03), 77 | 38–41.


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Integrating tumor and healthy epithelium in a micro-physiology multi-compartment approach to study renal cell carcinoma pathophysiology

Somova, Maryna; Simm, Stefan; Padmyastuti, Adventina; Ehrhardt, Jens; Schoon, Janosch...

Scientific Reports 14 (9357), 1.
DOI: 10.1038/s41598-024-60164-w


Open Access Peer Reviewed
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Mehr Lebensfreude durch Achtsamkeit und Resilienz

Kohls, Niko (2024)

Vortrag.



Wissenschaftlich belegt: 7 Strategien boostern Ihr mentales Immunsystem

Kohls, Niko (2024)

https://www.focus.de/experts/weniger-stress-mehr-gelassenheit-staerken-sie-ihr-mentales-immunsystem-experten-tipps-fuer-mehr-resilienz_id_259863156.html?utm_medium=social&utm_source=linkedin&utm_campaign=ec-livemail.



TAME II: A Modern Geographic Text Annotation Tool

Leidner, Jochen L.; Jung, Luca (2024)

Proceedings of the 21st International Symposium on Web and Wireless Geographical Information Systems (W2GIS 2024), June, 17-18, 2024, Yverdon-les-Bains, Switzerland , 95-104.
DOI: 10.1007/978-3-031-60796-7_7


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Improved screen content coding in VVC using soft context formation

Och, Hannah; Uddehal, Shabhrish; Strutz, Tilo; Kaup, André (2024)

IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'24), 14-19 April 2024, Seoul, South Korea, accepted for publication 2024, 3685 - 3689.
DOI: 10.1109/ICASSP48485.2024.10447125


Peer Reviewed
 

Screen content images typically contain a mix of natural and synthetic image parts. Synthetic sections usually are comprised of uniformly colored areas and repeating colors and patterns. In the VVC standard, these properties are exploited using Intra Block Copy and Palette Mode. In this paper, we show that pixel-wise lossless coding can outperform lossy VVC coding in such areas. We propose an enhanced VVC coding approach for screen content images using the principle of soft context formation. First, the image is separated into two layers in a block-wise manner using a learning-based method with four block features. Synthetic image parts are coded losslessly using soft context formation, the rest with VVC. We modify the available soft context formation coder to incorporate information gained by the decoded VVC layer for improved coding efficiency. Using this approach, we achieve Bjontegaard-Delta-rate gains of 4.98% on the evaluated data sets compared to VVC.

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Enhanced color palette modeling for lossless screen content

Och, Hannah; Uddehal, Shabhrish; Strutz, Tilo; Kaup, André (2024)

IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'24), 14-19 April 2024, Seoul, South Korea, accepted for publication 2024, 3670 - 3674.
DOI: 10.1109/ICASSP48485.2024.10446445


Peer Reviewed
 

Soft context formation is a lossless image coding method for screen content. It encodes images pixel by pixel via arithmetic coding by collecting statistics for probability distribution estimation. Its main pipeline includes three stages, namely a context model based stage, a color palette stage and a residual coding stage. Each stage is only employed if the previous stage is impossible since necessary statistics, e.g. colors or contexts, have not been learned yet. We propose the following enhancements: First, information from previous stages is used to remove redundant palette entries and prediction errors in subsequent stages. Additionally, implicitly known stage decision signals are no longer explicitly transmitted. These enhancements lead to an average bit rate decrease of 1.16% on the evaluated data. Compared to FLIF and HEVC, the proposed method needs roughly 0.28 and 0.17 bits per pixel less on average for 24-bit screen content images, respectively.

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Aerodynamische Untersuchung von Deltaflügeln bei Unterschall mit Ansys Discovery und Ansys CFX (Ein Beitrag für die Lehre)

Epple, Philipp; Fritsche, Manuel (2024)

CADFEM Conference 2024, Empowering Digital Engineering, 10.-11. April 2024, Darmstadt, Germany..



Bedarfs- und Bedürfnisanalyse hinsichtlich einer digitalen Bibliothek für den Öffentlichen Gesundheitsdienst [Conference Paper]

Hiller, Annika; Weiß, Katharina; Lisak-Wahl, Stefanie; Hinsche-Böckenholt, Andrea...

Das Gesundheitswesen 86 (S02), 70-71.
DOI: 10.1055/s-0044-1781783


Open Access Peer Reviewed
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International Social Work and Social Movements Claudia Lohrenscheit, Andrea Schmelz, Caroline Schmitt, Ute Straub (ed.)

Lohrenscheit , Claudia ; Schmelz, Andrea (2024)

1st edition 2024, 212.


Peer Reviewed

Experiments in News Bias Detection with Pre-Trained Neural Transformers

Menzner, T.; Leidner, Jochen L. (2024)

Proceedings of the 29th European Conference on Information Retrieval (ECIR 2024), Glasgow, Scotland, UK, March 24-28, 2024 IV, 270-284.
DOI: 10.1007/978-3-031-56066-8_22


Peer Reviewed
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