Gesamtliste aus der Hochschulbibliographie

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Eichfelder, Gabriele; Gerlach, Tobias; Warnow, Leo
A test instance generator for multiobjective mixed-integer optimization. - In: Mathematical methods of operations research, ISSN 1432-5217, Bd. 100 (2024), 1, S. 385-410

Application problems can often not be solved adequately by numerical algorithms as several difficulties might arise at the same time. When developing and improving algorithms which hopefully allow to handle those difficulties in the future, good test instances are required. These can then be used to detect the strengths and weaknesses of different algorithmic approaches. In this paper we present a generator for test instances to evaluate solvers for multiobjective mixed-integer linear and nonlinear optimization problems. Based on test instances for purely continuous and purely integer problems with known efficient solutions and known nondominated points, suitable multiobjective mixed-integer test instances can be generated. The special structure allows to construct instances scalable in the number of variables and objective functions. Moreover, it allows to control the resulting efficient and nondominated sets as well as the number of efficient integer assignments.



https://doi.org/10.1007/s00186-023-00826-z
De Souza Cardoso, Luís Fernando; Kimura, Bruno Yuji Lino; Zorzal, Ezequiel Roberto
Towards augmented and mixed reality on future mobile networks. - In: Multimedia tools and applications, ISSN 1573-7721, Bd. 83 (2024), 3, S. 9067-9102

Augmented and Mixed Reality (AR/MR) technologies enhance the human perception of the world by combining virtual and real environments. With the increase of mobile devices and the advent of 5G, this technology has the potential to become part of people’s life. This article aims to evaluate the impact of 5G and beyond mobile networks in the future of AR/MR. To attend to this objective, we surveyed four digital libraries to identify articles and reviews concerning AR/MR use based on mobile networks. The results describe the state-of-the-art of mobile AR/MR applications and the benefits and challenges of the technology. Finally, after the review, we propose a roadmap concerning AR/MR hardware and software development to run applications supported by future mobile networks.



https://doi.org/10.1007/s11042-023-15301-4
Döring, Nicola; Mikhailova, Veronika; Brandenburg, Karlheinz; Broll, Wolfgang; Groß, Horst-Michael; Werner, Stephan; Raake, Alexander
Digital media in intergenerational communication: status quo and future scenarios for the grandparent-grandchild relationship. - In: Universal access in the information society, ISSN 1615-5297, Bd. 23 (2024), 1, S. 379-394

Communication technologies play an important role in maintaining the grandparent-grandchild (GP-GC) relationship. Based on Media Richness Theory, this study investigates the frequency of use (RQ1) and perceived quality (RQ2) of established media as well as the potential use of selected innovative media (RQ3) in GP-GC relationships with a particular focus on digital media. A cross-sectional online survey and vignette experiment were conducted in February 2021 among N = 286 university students in Germany (mean age 23 years, 57% female) who reported on the direct and mediated communication with their grandparents. In addition to face-to-face interactions, non-digital and digital established media (such as telephone, texting, video conferencing) and innovative digital media, namely augmented reality (AR)-based and social robot-based communication technologies, were covered. Face-to-face and phone communication occurred most frequently in GP-GC relationships: 85% of participants reported them taking place at least a few times per year (RQ1). Non-digital established media were associated with higher perceived communication quality than digital established media (RQ2). Innovative digital media received less favorable quality evaluations than established media. Participants expressed doubts regarding the technology competence of their grandparents, but still met innovative media with high expectations regarding improved communication quality (RQ3). Richer media, such as video conferencing or AR, do not automatically lead to better perceived communication quality, while leaner media, such as letters or text messages, can provide rich communication experiences. More research is needed to fully understand and systematically improve the utility, usability, and joy of use of different digital communication technologies employed in GP-GC relationships.



https://doi.org/10.1007/s10209-022-00957-w
Köhler, Mona; Eisenbach, Markus; Groß, Horst-Michael
Few-shot object detection: a comprehensive survey. - In: IEEE transactions on neural networks and learning systems, ISSN 2162-2388, Bd. 0 (2023), 0, S. 1-21

Humans are able to learn to recognize new objects even from a few examples. In contrast, training deep-learning-based object detectors requires huge amounts of annotated data. To avoid the need to acquire and annotate these huge amounts of data, few-shot object detection (FSOD) aims to learn from few object instances of new categories in the target domain. In this survey, we provide an overview of the state of the art in FSOD. We categorize approaches according to their training scheme and architectural layout. For each type of approach, we describe the general realization as well as concepts to improve the performance on novel categories. Whenever appropriate, we give short takeaways regarding these concepts in order to highlight the best ideas. Eventually, we introduce commonly used datasets and their evaluation protocols and analyze the reported benchmark results. As a result, we emphasize common challenges in evaluation and identify the most promising current trends in this emerging field of FSOD.



https://doi.org/10.1109/TNNLS.2023.3265051
Hartbrich, Jakob; Weidner, Florian; Kunert, Christian; Arévalo Arboleda, Stephanie; Raake, Alexander; Broll, Wolfgang
Eye and face tracking in VR: avatar embodiment and enfacement with realistic and cartoon avatars. - In: MUM 2023, (2023), S. 270-278

Previous studies have explored the perception of various types of embodied avatars in immersive environments. However, the impact of eye and face tracking with personalized avatars is yet to be explored. In this paper, we investigate the impact of eye and face tracking on embodiment, enfacement, and the uncanny valley with four types of avatars using a VR-based mirroring task. We conducted a study (N=12) and created self-avatars with two rendering styles: a cartoon avatar (created in an avatar generator using a picture of the user’s face) and a photorealistic scanned avatar (created using a 3D scanner), each with and without eye and face tracking and respective adaptation of the mirror image. Our results indicate that adding eye and face tracking can be beneficial for certain enfacement scales (belonged), and we confirm that compared to a cartoon avatar, a scanned realistic avatar results in higher body ownership and increased enfacement (own face, belonging, mirror) - regardless of eye and face tracking. We critically discuss our experiences and outline the limitations of the applied hardware and software with respect to the provided level of control and the applicability for complex tasks such as displaying emotions. We synthesize these findings into a discussion about potential improvements for facial animation in VR and highlight the need for a better level of control, the integration of additional sensing and processing technologies, and an objective metric for comparing facial animation systems.



https://doi.org/10.1145/3626705.3627793
Hack, Jasmin; Jordan, Moritz; Schmitt, Alina; Raru, Melissa; Zorn, Hannes Sönke; Seyfarth, Alex; Eulenberger, Isabel; Geitner, Robert
Ilm-NMR-P31: an open-access 31P nuclear magnetic resonance database and data-driven prediction of 31P NMR shifts. - In: Journal of cheminformatics, ISSN 1758-2946, Bd. 15 (2023), 122, S. 1-12

This publication introduces a novel open-access 31P Nuclear Magnetic Resonance (NMR) shift database. With 14,250 entries encompassing 13,730 distinct molecules from 3,648 references, this database offers a comprehensive repository of organic and inorganic compounds. Emphasizing single-phosphorus atom compounds, the database facilitates data mining and machine learning endeavors, particularly in signal prediction and Computer-Assisted Structure Elucidation (CASE) systems. Additionally, the article compares different models for 31P NMR shift prediction, showcasing the database’s potential utility. Hierarchically Ordered Spherical Environment (HOSE) code-based models and Graph Neural Networks (GNNs) perform exceptionally well with a mean squared error of 11.9 and 11.4 ppm respectively, achieving accuracy comparable to quantum chemical calculations.



https://doi.org/10.1186/s13321-023-00792-y
Puch, Florian; Richter, Bastian
Influence of the processing on the properties of continuous fiber reinforced thermoplastic sheets prepared by extrusion. - In: AIP conference proceedings, ISSN 1551-7616, Bd. 2884 (2023), 1, 050005, S. 050005-1-050005-14

Continuous fiber reinforced thermoplastics (CFRT) are composite materials consisting of continuous fibers and a thermoplastic matrix and offer outstanding mechanical properties, low densities, short cycle times and recyclability. CFRT can be classified into unidirectional tapes and sheets utilizing various semi-finished textiles as reinforcement. CFRT sheets are of interest for area measured products or multiaxial loads. Various discontinuous and semi-continuous methods to prepare CFRP sheets are described in the literature. All these methods either feature high cycle times or high investment costs and require double melting of the polymer, e.g., first to produce a polymer film and second to produce the CFRT sheet. An energy efficient alternative to produce CFRT sheets is extrusion, which allows to spare one melting step. A twin-screw extruder melts the polymer, which is then conveyed by a melt pump to the film extrusion dies and applied to both sides of the semi-finished textile, which is wetted and consolidated using a calendar. Due to the high melt viscosity and the line load at the calendar the major challenge is to achieve full void-free impregnation of the semi-finished textile. The mechanical properties of a CFRT sheet are determined by fiber and void volume content. Hence, the influence of the processing conditions on the fiber and void volume content as well as the mechanical properties were examined applying a parametric study of the die temperature, the haul-off speed, and the gap between the calendar rolls. The properties of the extruded CFRT sheets were compared to compression molded sheets. The fiber volume content was directly adjusted by the haul-off speed and the extruder throughput. An increasing die temperature lowers the melt viscosity and results in an increased fiber volume content. Scanning electron microscopy shows complete macro impregnation between the fiber bundles but not completely wetted individual filaments within fiber bundles.



https://doi.org/10.1063/5.0168183
Räth, Timo; Onah, Ngozichukwuka; Sattler, Kai-Uwe
Interactive data cleaning for real-time streaming applications. - In: HILDA '23, (2023), 13, insges. 3 S.

The importance of data cleaning systems has continuously grown in recent years. Especially for real-time streaming applications, it is crucial, to identify and possibly remove anomalies in the data on the fly before further processing. The main challenge however lies in the construction of an appropriate data cleaning pipeline, which is complicated by the dynamic nature of streaming applications. To simplify this process and help data scientists to explore and understand the incoming data, we propose an interactive data cleaning system for streaming applications. In this paper, we list requirements for such a system and present our implementation to overcome the stated issues. Our demonstration shows, how a data cleaning pipeline can be interactively created, executed, and monitored at runtime. We also present several different tools, such as the automated advisor and the adaptive visualizer, that engage the user in the data cleaning process and help them understand the behavior of the pipeline.



https://doi.org/10.1145/3597465.3605229
Andrich, Aliya; Domahidi, Emese
Still facing the ‘paper ceiling’? : exploring gender differences in political news coverage of the last decade. - In: Journalism, ISSN 1741-3001, Bd. 0 (2023), 0, S. 14648849231215194

In the present study, we investigate gender bias against politicians in a large set of news articles (n = 1,139,571) published in major media outlets in the United States between 2010 and 2020 by tracing changes in reporting about 1,095 US politicians. Using topic modeling with latent Dirichlet allocation (LDA), we identify main policy-related topics in media reports. We find gender differences in the coverage of certain policy issues, with major imbalances explained by societal factors. Specifically, we show that women in high-level political positions receive less media coverage than their male counterparts and women in less powerful positions on economic and national security issues. However, women and men in less influential positions do not differ in the amount and type of reporting they garner. Since women are still underrepresented in leadership positions, the US media may inadvertently reflect and reinforce existing gender biases in society by devoting more attention to high-profile politicians, who are overwhelmingly male. Although our longitudinal analysis shows positive changes, the gender gap in reporting continues to exist.



https://doi.org/10.1177/14648849231215194
Sharifi Ghazijahani, Mohammad; Heyder, Florian; Schumacher, Jörg; Cierpka, Christian
Spatial prediction of the turbulent unsteady von Kármán vortex street using echo state networks. - In: Physics of fluids, ISSN 1089-7666, Bd. 35 (2023), 11, 115141, S. 115141-1-115141-15

The spatial prediction of the turbulent flow of the unsteady von Kármán vortex street behind a cylinder at Re = 1000 is studied. For this, an echo state network (ESN) with 6000 neurons was trained on the raw, low-spatial resolution data from particle image velocimetry. During prediction, the ESN is provided one half of the spatial domain of the fluid flow. The task is to infer the missing other half. Four different decompositions termed forward, backward, forward-backward, and vertical were examined to show whether there exists a favorable region of the flow for which the ESN performs best. Also, it was checked whether the flow direction has an influence on the network's performance. In order to measure the quality of the predictions, we choose the vertical velocity prediction of direction (VVPD). Furthermore, the ESN's two main hyperparameters, leaking rate (LR) and spectral radius (SR), were optimized according to the VVPD values of the corresponding network output. Moreover, each hyperparameter combination was run for 24 random reservoir realizations. Our results show that VVPD values are highest for LR ≈ 0.6, and quite independent of SR values for all four prediction approaches. Furthermore, maximum VVPD values of ≈ 0.83 were achieved for backward, forward-backward, and vertical predictions while for the forward case VVPDmax = 0.74 was achieved. We found that the predicted vertical velocity fields predominantly align with their respective ground truth. The best overall accordance was found for backward and forward-backward scenarios. In summary, we conclude that the stable quality of the reconstructed fields over a long period of time, along with the simplicity of the machine learning algorithm (ESN), which relied on coarse experimental data only, demonstrates the viability of spatial prediction as a suitable method for machine learning application in turbulence.



https://doi.org/10.1063/5.0172722