@inproceedings{45776, author = {{Ecker, Wolfgang and Krstic, Milos and Ulbricht, Markus and Mauderer, Andreas and Jentzsch, Eyck and Koch, Andreas and Koppelmann, Bastian and Müller, Wolfgang and Sadiye, Babak and Bruns, Niklas and Drechsler, Rolf and Müller-Gritschneder, Daniel and Schlamelcher, Jan and Grüttner, Kim and Bormann, Jörg and Kunz, Wolfgang and Heckmann, Reinhold and Angst, Gerhard and Wimmer, Ralf and Becker, Bernd and Faller, Tobias and Palomero Bernardo, Paul and Brinkmann, Oliver and Partzsch, Johannes and Mayr, Christian}}, booktitle = {{Scale4Edge – Scaling RISC-V for Edge Applications}}, location = {{ Barcelona, Spain,}}, title = {{{Scale4Edge – Scaling RISC-V for Edge Applications}}}, year = {{2023}}, } @article{45782, abstract = {{The development of automotive components with reduced greenhouse gas (GHG) emissions is needed to reduce overall vehicle emissions. Life Cycle Engineering (LCE) based on Life Cycle Assessment (LCA) supports this by providing holistic information and improvement potentials regarding eco-efficient products. Key factors influencing LCAs of automotive components, such as material production, will change in the future. First approaches for integrating future scenarios for these key factors into LCE already exist, but they only consider a limited number of parameters and scenarios. This work aims to develop a method that can be practically applied in the industry for integrating prospective LCAs (pLCA) into the LCE of automotive components, considering relevant parameters and consistent scenarios. Therefore, pLCA methods are further developed to investigate the influence of future scenarios on the GHG emissions of automotive components. The practical application is demonstrated for a vehicle component with different design options. This paper shows that different development paths of the foreground and background system can shift the ecological optimum of design alternatives. Therefore, future pathways of relevant parameters must be considered comprehensively to reduce GHG emissions of future vehicles. This work contributes to the methodological and practical integration of pLCA into automotive development processes and provides quantitative results.}}, author = {{Grenz, Julian and Ostermann, Moritz and Käsewieter, Karoline and Cerdas, Felipe and Marten, Thorsten and Herrmann, Christoph and Tröster, Thomas}}, issn = {{2071-1050}}, journal = {{Sustainability}}, keywords = {{prospective LCA, life cycle engineering (LCE), lightweight design, automotive components, body parts, circular economy, steel, aluminum, hybrid materials, fiber metal laminates}}, number = {{13}}, publisher = {{MDPI AG}}, title = {{{Integrating Prospective LCA in the Development of Automotive Components}}}, doi = {{10.3390/su151310041}}, volume = {{15}}, year = {{2023}}, } @inproceedings{45793, abstract = {{The global megatrends of digitization and sustainability lead to new challenges for the design and management of technical products in industrial companies. Product management - as the bridge between market and company - has the task to absorb and combine the manifold requirements and make the right product-related decisions. In the process, product management is confronted with heterogeneous information, rapidly changing portfolio components, as well as increasing product, and organizational complexity. Combining and utilizing data from different sources, e.g., product usage data and social media data leads to promising potentials to improve the quality of product-related decisions. In this paper, we reinforce the need for data-driven product management as an interdisciplinary field of action. The state of data-driven product management in practice was analyzed by conducting workshops with six manufacturing companies and hosting a focus group meeting with experts from different industries. We investigate the expectations and derive requirements leading us to open research questions, a vision for data-driven product management, and a research agenda to shape future research efforts.}}, author = {{Grigoryan, Khoren and Fichtler, Timm and Schreiner, Nick and Rabe, Martin and Panzner, Melina and Kühn, Arno and Dumitrescu, Roman and Koldewey, Christian}}, booktitle = {{Procedia CIRP 33}}, keywords = {{Product Management, Data Analytics, Data-Driven Design, Product-related data, Lifecycle Data, Tool-support}}, location = {{Sydney}}, title = {{{Data-Driven Product Management: A Practitioner-Driven Research Agenda}}}, year = {{2023}}, } @article{45807, abstract = {{Abstract Background Occupational health interventions for leaders are underrepresented in small and medium-sized enterprises (SMEs). When creating and developing effective occupational health interventions, identification of the specific needs of the target group is regarded as an essential step before planning an intervention. Therefore, the aim of this study was (1) to examine the subjectively experienced work-related stressors of leaders in small and medium-sized IT and technological services enterprises, (2) to explore coping behaviors leaders use to deal with the experienced work-related stressors, (3) to investigate resources supporting the coping process and (4) to identify potentially self-perceived consequences resulting from the experienced stressors. Methods Ten semi-structured interviews with leaders in small and medium-sized IT and technological services enterprises were conducted. The interviews were transcribed and analyzed with content-structuring qualitative content analysis in accordance to Kuckartz. Results Leaders in small and medium-sized IT and technological services enterprises experience various stressors caused by work organization as well as industry-related stressors and other work-related stressors. To address the experienced stressors, leaders apply problem focused coping behaviors (e.g. performing changes on structural and personal level), emotional focused coping behaviors (e.g. balancing activities, cognitive restructuring) as well as the utilization of social support. Helpful resources for the coping process include organizational, social and personal resources. As a result of the experienced work-related stressors, interviewees stated to experience different health impairments, negative effects on work quality as well as neglect of leisure activities and lack of time for family and friends. Conclusion The identified experienced work-related stressors, applied coping behaviors, utilized resources and emerging consequences underpin the urgent need for the development and performance of health-oriented leadership interventions for leaders in small and medium- sized IT and technological services. The results of this study can be used when designing a target-oriented intervention for the examined target group. }}, author = {{Dannheim, Indra and Buyken, Anette and Kroke, Anja}}, issn = {{1471-2458}}, journal = {{BMC Public Health}}, keywords = {{Public Health, Environmental and Occupational Health}}, number = {{1}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Work-related stressors and coping behaviors among leaders in small and medium-sized IT and technological services enterprises}}}, doi = {{10.1186/s12889-023-15581-3}}, volume = {{23}}, year = {{2023}}, } @article{45806, abstract = {{Abstract Objective: To systematically review the impact of choice architecture interventions (CAI) on the food choice of healthy adolescents in a secondary school setting. Factors potentially contributing to the effectiveness of CAI types and numbers implemented and its long-term success were examined. Design: PUBMED and Web of Science were systematically searched in October 2021. Publications were included following predefined inclusion criteria and grouped according to number and duration of implemented interventions. Intervention impact was determined by systematic description of the reported quantitative changes in food choice and/or consumption. Intervention types were compared with regards to food selection and sustained effects either during or following the intervention. Setting: CAI on food choice of healthy adolescents in secondary schools. Participants: Not applicable Results: Fourteen studies were included; four randomized controlled trials and five each of controlled or uncontrolled pre-post design, respectively. Four studies implemented a single CAI type, with ten implementing > 1. Three studies investigated CAI effects over the course of a school year either by continuous or repeated data collection, while ten studies’ schools were visited on selected days during intervention. Twelve studies reported desired changes in overall food selection, yet effects were not always significant, and appeared less conclusive for longer term studies. Conclusions: This review found promising evidence that CAI can be effective in encouraging favorable food choices in healthy adolescents in a secondary school setting. However, further studies designed to evaluate complex interventions are needed. }}, author = {{Schulte, Eva A. and Winkler, Gertrud and Brombach, Christine and Buyken, Anette}}, issn = {{1368-9800}}, journal = {{Public Health Nutrition}}, keywords = {{Public Health, Environmental and Occupational Health, Nutrition and Dietetics, Medicine (miscellaneous)}}, pages = {{1--23}}, publisher = {{Cambridge University Press (CUP)}}, title = {{{Choice architecture interventions promoting sustained healthier food choice and consumption by students in a secondary school setting: A systematic review of intervention studies}}}, doi = {{10.1017/s1368980023001118}}, year = {{2023}}, } @article{45810, abstract = {{ Background: Establishing a healthy lifestyle has a great potential to reduce the prevalence of non-communicable diseases (NCDs) and their risk factors. NCDs contribute immensely to the economic costs of the health care system arising from therapy, medication use, and productivity loss. Aim: The aim of this study was to evaluate the effect of the Healthy Lifestyle Community Program (cohort 2; HLCP-2) on medication use and consequently on medication costs for selected NCDs (diabetes, hypertension, and dyslipidemia). Methods: Data stem from a 24-month non-randomised, controlled intervention trial aiming to improve risk factors for NCDs. Participants completed questionnaires at six measurement time points assessing medication use, from which costs were calculated. The following medication groups were included in the analysis as NCD medication: glucose-lowering medications (GLM), antihypertensive drugs (AHD) and lipid-lowering drugs (LLD). Statistical tests for inter- and intra-group comparison and multiple regression analysis were performed. Results: In total, 118 participants (intervention group [IG]: n = 79; control group [CG]: n = 39) were considered. Compared to baseline medication use decreased slightly in the IG and increased in the CG. Costs for NCD medication were significantly lower in the IG than in the CG after 6 ( p = 0.004), 12 ( p = 0.040), 18 ( p = 0.003) and 24 months ( p = 0.008). After multiple regression analysis and adjusting for confounders, change of costs differed significantly between the groups in all final models. Conclusion: The HLCP-2 was able to moderately prevent an increase of medication use and thus reduce costs for medication to treat NCDs with the greatest impact on AHD. Trial registration German Clinical Trials Register DRKS ( www.drks.de ; reference: DRKS00018775). }}, author = {{Kranz, Ragna-Marie and Kettler, Carmen and Anand, Corinna and Koeder, Christian and Husain, Sarah and Schoch, Nora and Buyken, Anette and Englert, Heike}}, issn = {{0260-1060}}, journal = {{Nutrition and Health}}, keywords = {{Nutrition and Dietetics, General Medicine, Medicine (miscellaneous)}}, publisher = {{SAGE Publications}}, title = {{{Effect of a controlled lifestyle intervention on medication use and costs: The Healthy Lifestyle Community Program (cohort 2)}}}, doi = {{10.1177/02601060231164665}}, year = {{2023}}, } @article{45813, abstract = {{A previous follow-up of the GINIplus study showed that breastfeeding could protect against early eczema. However, effects diminished in adolescence, possibly indicating a “rebound effect” in breastfed children after initial protection. We evaluated the role of early eczema until three years of age on allergies until young adulthood and assessed whether early eczema modifies the association between breastfeeding and allergies. Data from GINIplus until 20-years of age (N = 4058) were considered. Information on atopic eczema, asthma, and rhinitis was based on reported physician’s diagnoses. Adjusted Odds Ratios (aOR) were modelled by using generalized estimating equations. Early eczema was associated with eczema (aORs = 3.2–14.4), asthma (aORs = 2.2–2.7), and rhinitis (aORs = 1.2–2.7) until young adulthood. For eczema, this association decreased with age (p-for-interaction = 0.002–0.006). Longitudinal models did not show associations between breastfeeding and the respective allergies from 5 to 20 years of age. Moreover, early eczema generally did not modify the association between milk feeding and allergies except for rhinitis in participants without family history of atopy. Early eczema strongly predicts allergies until young adulthood. While preventive effects of full breastfeeding on eczema in infants with family history of atopy does not persist until young adulthood, the hypothesis of a rebound effect after initial protection cannot be confirmed.}}, author = {{Libuda, Lars and Filipiak-Pittroff, Birgit and Standl, Marie and Schikowski, Tamara and von Berg, Andrea and Koletzko, Sibylle and Bauer, Carl-Peter and Heinrich, Joachim and Berdel, Dietrich and Gappa, Monika}}, issn = {{2072-6643}}, journal = {{Nutrients}}, keywords = {{Food Science, Nutrition and Dietetics}}, number = {{12}}, publisher = {{MDPI AG}}, title = {{{Full Breastfeeding and Allergic Diseases—Long-Term Protection or Rebound Effects?}}}, doi = {{10.3390/nu15122780}}, volume = {{15}}, year = {{2023}}, } @inproceedings{31880, abstract = {{The notion of neural collapse refers to several emergent phenomena that have been empirically observed across various canonical classification problems. During the terminal phase of training a deep neural network, the feature embedding of all examples of the same class tend to collapse to a single representation, and the features of different classes tend to separate as much as possible. Neural collapse is often studied through a simplified model, called the unconstrained feature representation, in which the model is assumed to have "infinite expressivity" and can map each data point to any arbitrary representation. In this work, we propose a more realistic variant of the unconstrained feature representation that takes the limited expressivity of the network into account. Empirical evidence suggests that the memorization of noisy data points leads to a degradation (dilation) of the neural collapse. Using a model of the memorization-dilation (M-D) phenomenon, we show one mechanism by which different losses lead to different performances of the trained network on noisy data. Our proofs reveal why label smoothing, a modification of cross-entropy empirically observed to produce a regularization effect, leads to improved generalization in classification tasks.}}, author = {{Nguyen, Duc Anh and Levie, Ron and Lienen, Julian and Kutyniok, Gitta and Hüllermeier, Eyke}}, booktitle = {{International Conference on Learning Representations, ICLR}}, location = {{Kigali, Ruanda}}, title = {{{Memorization-Dilation: Modeling Neural Collapse Under Noise}}}, year = {{2023}}, } @unpublished{45814, abstract = {{Label noise poses an important challenge in machine learning, especially in deep learning, in which large models with high expressive power dominate the field. Models of that kind are prone to memorizing incorrect labels, thereby harming generalization performance. Many methods have been proposed to address this problem, including robust loss functions and more complex label correction approaches. Robust loss functions are appealing due to their simplicity, but typically lack flexibility, while label correction usually adds substantial complexity to the training setup. In this paper, we suggest to address the shortcomings of both methodologies by "ambiguating" the target information, adding additional, complementary candidate labels in case the learner is not sufficiently convinced of the observed training label. More precisely, we leverage the framework of so-called superset learning to construct set-valued targets based on a confidence threshold, which deliver imprecise yet more reliable beliefs about the ground-truth, effectively helping the learner to suppress the memorization effect. In an extensive empirical evaluation, our method demonstrates favorable learning behavior on synthetic and real-world noise, confirming the effectiveness in detecting and correcting erroneous training labels.}}, author = {{Lienen, Julian and Hüllermeier, Eyke}}, booktitle = {{arXiv:2305.13764}}, title = {{{Mitigating Label Noise through Data Ambiguation}}}, year = {{2023}}, } @inproceedings{45812, author = {{Özcan, Leon and Fichtler, Timm and Kasten, Benjamin and Koldewey, Christian and Dumitrescu, Roman}}, keywords = {{Digital Platform, Platform Strategy, Strategic Management, Platform Life Cycle, Interview Study, Business Model, Business-to-Business, Two-sided Market, Multi-sided Market}}, location = {{Ljubljana}}, title = {{{Interview Study on Strategy Options for Platform Operation in B2B Markets}}}, year = {{2023}}, }