Refine
Year of publication
Document Type
- Article (1841)
- conference proceeding (article) (1689)
- Part of a Book (569)
- conference proceeding (presentation, abstract) (270)
- Book (163)
- conference talk (138)
- Report (123)
- Review (100)
- Preprint (53)
- Working Paper (51)
- conference proceeding (volume) (34)
- Doctoral Thesis (24)
- Edited collection (21)
- Part of Periodical (20)
- Master's Thesis (15)
- Lecture (12)
- Bachelor-/Diplom Thesis (11)
- Patent (10)
- Other (9)
- Moving Images (7)
- Study Thesis (4)
- Sound (3)
- Course Material (2)
- Habilitation (2)
Language
Is part of the Bibliography
- no (5171)
Keywords
- Simulation (38)
- Digitalisierung (31)
- Erneuerbare Energien (28)
- Energiewende (27)
- field emission (24)
- Bildgebendes Verfahren (22)
- Deep Learning (22)
- Deutschland (22)
- Klimaneutralität (22)
- Power-to-Gas (21)
Institute
- Fakultät Angewandte Sozial- und Gesundheitswissenschaften (1303)
- Fakultät Informatik und Mathematik (1144)
- Fakultät Maschinenbau (913)
- Fakultät Elektro- und Informationstechnik (805)
- Institut für Sozialforschung und Technikfolgenabschätzung (IST) (554)
- Labor Empirische Sozialforschung (458)
- Fakultät Angewandte Natur- und Kulturwissenschaften (404)
- Fakultät Bauingenieurwesen (357)
- Labor für Technikfolgenabschätzung und Angewandte Ethik (LaTe) (312)
- Laboratory for Safe and Secure Systems (LAS3) (278)
Begutachtungsstatus
- peer-reviewed (1578)
- begutachtet (96)
The success of surgical treatment for fractures hinges on various factors, notably accurate surgical indication. The process of developing and certifying a new osteosynthesis device is a lengthy and costly process that requires multiple cycles of review and validation. Current methods, however, often rely on predecessor standards rather than physiological loads in specific anatomical locations. This study aimed to determine actual loads experienced by an osteosynthesis plate, exemplified by a standard locking plate for the femoral shaft, utilizing finite elements analysis (FEA) and to obtain the bending moments for implant development standard tests. A protocol was developed, involving the creation and validation of a fractured femur model fixed with a locking plate, mechanical testing, and FEA. The model’s validation demonstrated exceptional accuracy in predicting deformations, and the FEA revealed peak stresses in the fracture bridging zone. Results of a parametric analysis indicate that larger fracture gaps significantly impact implant mechanical behavior, potentially compromising stability. This study underscores the critical need for realistic physiological conditions in implant evaluations, providing an innovative translational approach to identify internal loads and optimize implant designs. In conclusion, this research contributes to enhancing the understanding of implant performance under physiological conditions, promoting improved designs and evaluations in fracture treatments.
Designing textile Antennas is still challenging, as normal antenna design does not account for the textile nature of the materials: The e-Tex project investigates knitted and embroidered antennas to enhance the design process. The presentation shows first investigations in particular of knitted structures using measurement, simulation and theoretical models. In addition, plans to include measured models in simulation, in order to yield accurate results, will be presented.
In einer vorrangegangenen Studie wurde der Einfluss psychoakustischer Parameter auf Präferenzurteile für konsonante und dissonante Geräusche untersucht. Diese Geräusche hatten die gleiche Lautheit und basierten auf einem festen Rauschhintergrund und eingebetteten hochfrequenten Tonkomponenten. Es zeigte sich, dass die Präferenzurteile eines Probandenkollektives durch ebenfalls erhobene Subjektivurteile zu Schärfe, Tonhaltigkeit und Dissonanz mit hoher Präzision vorhergesagt werden konnten.Durch das angewandte Versuchsdesign konnte diese rein auf Subjektivbeurteilungen bestehende Vorhersage mit einer instrumentellen Vorhersage der Präferenzurteile verglichen werden. Der Vergleich ergab einen niedrigeren Korrelationskoeffizienten für die modellbasierte Vorhersage, was auch durch die sehr niedrige Korrelation (R2<0,2) der berechneten Schärfe nach DIN45692 mit den Schärfe-Subjektivurteilen zu begründen war. Eine mögliche Erklärung der unzureichenden Prognose der Schärfeurteile könnte in der Bewertungsstrategie der Proband:innen zu finden sein. Für die getesteten Geräusche mit auffälligen tonalen Komponenten könnte statt der Schärfe des Gesamtgeräuschs nur die Schärfe des tonalen Geräuschobjekts berücksichtigt worden sein. Die Schärfe-Analyse der auf ihren tonalen Anteil reduzierten Signale zeigt eine sehr gute Übereinstimmung mit den Subjektivurteilen, was die Hypothese einer Trennung von Ton- und Rauschobjekten unterstützt. Es wird diskutiert, ob und wie das Paradigma der akustischen Objekttrennung in der Modellierung psychoakustischer Empfindungsgrößen Anwendung finden kann.
Context:
Causal probabilistic graph-based models have gained widespread utility, enabling the modeling of cause-and-effect relationships across diverse domains. With their rising adoption in new areas, such as safety analysis of complex systems, software engineering, and machine learning, the need for an integrated lifecycle framework akin to DevOps and MLOps has emerged. Currently, such a reference for organizations interested in employing causal engineering is missing. This lack of guidance hinders the incorporation and maturation of causal methods in the context of real-life applications.
Objective:
This work contextualizes causal model usage across different stages and stakeholders and outlines a holistic view of creating and maintaining them within the process landscape of an organization.
Method:
A novel lifecycle framework for causal model development and application called CausalOps is proposed. By defining key entities, dependencies, and intermediate artifacts generated during causal engineering, a consistent vocabulary and workflow model to guide organizations in adopting causal methods are established.
Results:
Based on the early adoption of the discussed methodology to a real-life problem within the automotive domain, an experience report underlining the practicability and challenges of the proposed approach is discussed.
Conclusion:
It is concluded that besides current technical advancements in various aspects of causal engineering, an overarching lifecycle framework that integrates these methods into organizational practices is missing. Although diverse skills from adjacent disciplines are widely available, guidance on how to transfer these assets into causality-driven practices still need to be addressed in the published literature. CausalOps’ aim is to set a baseline for the adoption of causal methods in practical applications within interested organizations and the causality community.
Hintergrund:
In der Physiotherapie existieren zahlreiche Assessments zur Befunderhebung der unteren Extremität bei Kniepatient*innen. Damit können praktizierende Physiotherapeut*innen das Problem der Patient*innen genauer erfassen und dementsprechend die Behandlung aufbauen. Das Ergebnis der Beurteilung einer Patient#ast#in hängt oftmals stark von den Bewertenden ab. Fragestellung: Deshalb überprüft die Studie die Hypothese, ob innerhalb einer Tester*innengruppe mehr gleiche Ausgleichsbewegung bei der Befundung des Sit-to-Stand (STS) anhand von Videomaterial erkannt werden, als es der Standard erwarten würde.
Methode:
In dieser beobachtenden klinischen Querschnittsstudie wurde die Vergleichbarkeit der Befundergebnisse von 4 Therapeut*innen zum abgewandelten STS untersucht. Die zu beurteilenden Proband*innen wurden während der Durchführung des abgewandelten STS standardisiert in der Frontal- und Sagittalebene gefilmt und mittels eines Fragebogens von Berufsanfänger*innen der Physiotherapie beurteilt. Bei dem erstellten Fragebogen handelte es sich um eine systematische Abfrage aller möglichen Bewegungen der großen Gelenke der unteren Extremität mit dichotomen Antwortmöglichkeiten. Eingeschlossen wurden Proband*innen mit oder ohne diagnostizierten Knieproblemen, die älter als 18 Jahre und deutschsprachig sind. Proband*innen mit einschränkenden Nebenerkrankungen wie z.B. neurologische Erkrankungen und Operationen in den letzten 6 Monaten wurden ausgeschlossen. Anschließend wurden die Antworten der Therapeut*innen auf die Übereinstimmung der Ergebnisse überprüft.
Ergebnisse:
Die vollständigen Ergebnisse werden auf dem Poster nachgereicht. Die Interrater-Reliabilität wird mit Hilfe des Fleiss’ Kappa bestimmt. Voraussichtlich werden 25 Proband*innen in die Studie eingeschlossen.
Schlussfolgerung:
Mittels der Ergebnisse soll auf die Interrater-Reliabilität von Bewegungsbefunden des abgewandelten STS bei Kniepatient*innen geschlossen werden
Interpretable Machine Learning for Mode Choice Modeling on Tracking-Based Revealed Preference Data
(2024)
Mode choice modeling is imperative for predicting and understanding travel behavior. For this purpose, machine learning (ML) models have increasingly been applied to stated preference and traditional self-recorded revealed preference data with promising results, particularly for extreme gradient boosting (XGBoost) and random forest (RF) models. Because of the rise in the use of tracking-based smartphone applications for recording travel behavior, we address the important and unprecedented task of testing these ML models for mode choice modeling on such data. Furthermore, as ML approaches are still criticized for leading to results that are hard to understand, we consider it essential to provide an in-depth interpretability analysis of the best-performing model. Our results show that the XGBoost and RF models far outperform a conventional multinomial logit model, both overall and for each mode. The interpretability analysis using the Shapley additive explanations approach reveals that the XGBoost model can be explained well at the overall and mode level. In addition, we demonstrate how to analyze individual predictions. Lastly, a sensitivity analysis gives insight into the relative importance of different data sources, sample size, and user involvement. We conclude that the XGBoost model performs best, while also being explainable. Insights generated by such models can be used, for instance, to predict mode choice decisions for arbitrary origin–destination pairs to see which impacts infrastructural changes would have on the mode share.
In a number of tomographic applications, data cannot be fully acquired, resulting in severely underdetermined image reconstruction. Conventional methods in such cases lead to reconstructions with significant artifacts. To overcome these artifacts, regularization methods are applied that incorporate additional information. An important example is TV reconstruction, which is known to be efficient in compensating for missing data and reducing reconstruction artifacts. On the other hand, tomographic data are also contaminated by noise, which poses an additional challenge. The use of a single regularizer must therefore account for both the missing data and the noise. A particular regularizer may not be ideal for both tasks. For example, the TV regularizer is a poor choice for noise reduction over multiple scales, in which case ℓ1 curvelet regularization methods are well suited. To address this issue, in this paper, we present a novel variational regularization framework that combines the advantages of different regularizers. The basic idea of our framework is to perform reconstruction in two stages. The first stage is mainly aimed at accurate reconstruction in the presence of noise, and the second stage is aimed at artifact reduction. Both reconstruction stages are connected by a data proximity condition. The proposed method is implemented and tested for limited-view CT using a combined curvelet–TV approach. We define and implement a curvelet transform adapted to the limited-view problem and illustrate the advantages of our approach in numerical experiments.
This research presents two laser-based photoacoustic approaches for analyzing exhaled breath isoprene and acetone. The integration of a PTR-ToF-MS as a reference device ensured the reliability and accuracy of the PAS systems that is based on an ICL for isoprene and a QCL for acetone detection. The calibration yielded limits of detection of 26.9 ppbV and 1.7 ppbV, respectively, and corresponding normalized noise equivalent absorption coefficients (NNEAs) of 5.0E-9 Wcm-1Hz-0.5 and 4.9E-9 Wcm-1Hz-0.5. Laboratory as well as real breath sample measurements from alveolar breath revealed a robust system performance, with only one outlier within the static isoprene measurements. However, discrepancies emerged under dynamic breath sampling conditions, emphasizing the need for further optimization. Especially by knowing the dynamic nature and endogenous origin of exhaled isoprene our findings highlight the potential of breath analysis for non-invasive physio-metabolic and pathophysiological monitoring towards point-of-care devices.
Enhancing Decision-Making for Human-Centered Construction Robotics: A Methodological Framework
(2024)
While the Architecture, Engineering, and Construction (AEC) industry is increasingly aware of the rising demands for productivity and human-centered construction improvements, the holistic adoption of robotics as a fundamental strategy to address these challenges has not yet reached comprehensive fruition. This paper therefore introduces a methodological framework aiming to address the industry's pressing need for a systematic approach for assessing the feasibility of integrating robotics into human-centered construction processes. It aims to enhance decision-making regarding the degree of automation in human-centered construction processes, ranging from partial to full robotization or non-robotization. The framework is characterized by a more holistic end-to-end data-/workflow and therefore adopts a multifaceted approach, leveraging BIM-based planning methodologies and integrating new technologies [e.g., Motion Capturing (MoCap), work process simulation software incorporating Digital Human Models (DHM), self-developed conversion/interfacing software and more] that have not been widely used in the industry to date. Subsequently, the framework is evaluated in a real-life bricklaying construction process to ensure a more application-based approach. Overall, the framework advances current construction processes with a more inclusive and conscious technology infill to empower construction professionals with the workflow and corresponding tools necessary for the practical integration of robotics into human-centered construction processes.