Filtern
Erscheinungsjahr
- 2021 (116) (entfernen)
Dokumenttyp
- Wissenschaftlicher Artikel (66)
- Video (16)
- Konferenzveröffentlichung (11)
- Buch (Monographie) (5)
- Teil eines Buches (Kapitel) (5)
- Sonstiges (4)
- Preprint (4)
- Beitrag zu einer (nichtwissenschaftlichen) Zeitung oder Zeitschrift (1)
- Dissertation (1)
- Bericht (1)
Schlagworte
- Robotik (17)
- Flugkörper (11)
- UAV (11)
- Rettungsrobotik (8)
- Rasenmäher (4)
- Journalismus (2)
- 3D-Printer (1)
- Aerosol (1)
- Aggregation-prone (1)
- Arbeit, Kapital und Staat (1)
Institut
- Informatik und Kommunikation (28)
- Wirtschaftsrecht (22)
- Institut für biologische und chemische Informatik (13)
- Wirtschaft und Informationstechnik Bocholt (10)
- Wirtschaft Gelsenkirchen (7)
- Elektrotechnik und angewandte Naturwissenschaften (5)
- Maschinenbau Bocholt (5)
- Westfälisches Energieinstitut (5)
- Westfälisches Institut für Gesundheit (2)
- Wirtschaftsingenieurwesen (2)
Background: By reviewing image quality and diagnostic perception, the suitability of a statistical model-based iterative reconstruction algorithm in conjunction with low-dose computed tomography for lung cancer screening is investigated.
Methods: Artificial lung nodules shaped as spheres and spiculated spheres made from material with calibrated Hounsfield units were attached on marked positions in the lung structure of anthropomorphic phantoms. The phantoms were scanned using standard high contrast, and two low-dose computed tomography protocols: low-dose and ultra-low-dose. For the reconstruction, the filtered back projection and the iterative reconstruction algorithm ADMIRE at different strength levels (S1–S5) and the kernels Bl57, Br32, Br69 were used. Expert radiologists assessed image quality by performing 4-field-ranking tests and reading all image series to examine the aptitude for the detectability of lung nodules. Signal-to-noise ratio was investigated as objective image quality parameter.
Results: In ranking tests for lung foci detection expert radiologists prefer medium to high iterative reconstruction strength levels. For the standard clinical kernel Bl57 and varying phantom diameter, a noticeable preference for S4 was detected. Experienced radiologists graded filtered back projection reconstructed images with the highest perceptibility. Less experienced readers assessed filtered back projection and iterative reconstruction equally with the highest grades for the Bl57 kernel. Independently of the dose protocol, the signal-to-noise ratio increases with the iterative reconstruction strength level, specifically for Br69 and Bl57.
Conclusions: Subjective image perception does not significantly correlate with the experience of the radiologist, which presumably mirrors reader’s training and accustomed reading adjustments. Regarding signal-to-noise ratio, iterative reconstruction outperforms filtered back projection for spheres and spiculated spheres. Iterative reconstruction matters. It promises to be an alternative to filtered back projection allowing for lung-cancer screening at markedly decreased radiation exposure but comparable or even improved image quality.
This introduction to a special issue about concepts and facets of entrepreneurial diversity serves as a starting point for further discussion and research in this field. For this purpose, we provide information about the roots of the study of diversity and current trends in entrepreneurship research and present a frame for (researching) entrepreneurial diversity. Additionally, we briefly summarize the three papers selected for inclusion in this special issue. Together, they offer insights into the intersections of different diversity dimensions, personality as a deep dimension of team composition, and a general critical reflection on the conceptualization of entrepreneurial diversity. Taken together, the papers in this special issue present new findings and contribute to further advancing the long overdue research on and discussion about diversity in the field of entrepreneurship.
This technical report is about the mission and the experience gained during the reconnaissance of an industrial hall with hazardous substances after a major fire in Berlin. During this operation, only UAVs and cameras were used to obtain information about the site and the building. First, a geo-referenced 3D model of the building was created in order to plan the entry into the hall. Subsequently, the UAVs were used to fly in the heavily damaged interior and take pictures from inside of the hall. A 360° camera mounted under the UAV was used to collect images of the surrounding area especially from sections that were difficult to fly into. Since the collected data set contained similar images as well as blurred images, it was cleaned from non-optimal images using visual SLAM, bundle adjustment and blur detection so that a 3D model and overviews could be calculated. It was shown that the emergency services were not able to extract the necessary information from the 3D model. Therefore, an interactive panorama viewer with links to other 360° images was implemented where the links to the other images depends on the semi dense point cloud and located camera positions of the visual SLAM algorithm so that the emergency forces could view the surroundings.
Description and Analysis of Glycosidic Residues in the Largest Open Natural Products Database
(2021)
This paper describes a new concept and experiences of a distributed interdisciplinary learning programme for students across continents. The aim is to provide students with a truly Global Intercultural Project Experience (GIPE) by working together with peers from around the world, and solving real-life client’s problems. We have received seed-funding for four annual projects to engage students from Germany (Europe), Namibia (Africa), Indonesia (Asia), and Peru (Latin-America). In 2020, 30 students from four continents engaged in a one-semester distributed software development project for a Namibian client. Despite Covid-19 they successfully completed the project expressing deep appreciation for the learning opportunities overcoming challenges of working across wide-spread time zones, cultures, changing requirements, and various technical challenges. Considering the vast learning benefits, we suggest to incorporate such projects in all tertiary education curricula across the globe.
Competency-oriented exams offer a wide range of advantages, especially where the use and mastery of third-party applications and tools play an important role. Therefore, we developed a competency-oriented setup for both our programming classes and exams ensuring their constructive alignment.
Exams were moved to the computer lab and designed to test both conceptional skills as well as the use of state-of-the-art programming tools. At the peak of the COVID-19 pandemic, when exams had to be moved from lab to online, we needed to design an online setup for our practical programming exams preserving the competency-oriented approach and its constructive alignment as well as the validity, reliability and fairness of the exams. The key was to use the same online tools that have been introduced
for running lectures and practical classes offering almost the same learning experience as before the pandemic. However, to ensure the validity and fairness of the exams, some kind of online supervision needed to be implemented as technical solutions were found to be either unusable or not working
properly in our case. This paper discusses the driving factors, the resulting technical and organizational setup as well as students’ feedback and lessons learned for further improvements. Therefore, COVID-19 has not been able to ruin our competency-oriented programming exams.
In Kollaboration mit dem Fachbereich Maschinenbau wurde eine prototypische Lösung zur Visualisierung der Interaktion zwischen Mensch und Maschine bei kooperativen Arbeiten entwickelt. Der Prototyp wurde in der Programmiersprache C++ auf Basis der Unreal Engine 4 realisiert und soll als Grundlage für weitere Forschungen im Bereich der Mensch-Roboter-Kollaboration dienen. Zur Echtzeitsimulation der Maschinen wurde eine Anbindung basierend auf dem Protokoll OPC UA integriert, sodass eine Kopplung mit Enterprise-Applikationen wie Siemens NX MCD und ABB RobotStudio möglich ist. Für eine realitätsgetreue Darstellung können die Maschinen in der virtuellen Realität abgebildet werden. Die Visualisierung eines Menschen erfolgt durch Einbindung der Microsoft Azure Kinect, wodurch eine Person durch eine farbliche Punktwolke oder ein Skelett angezeigt werden kann.
Flying insects employ elegant optical-flow-based strategies to solve complex tasks such as landing or obstacle avoidance. Roboticists have mimicked these strategies on flying robots with only limited success, because optical flow (1) cannot disentangle distance from velocity and (2) is less informative in the highly important flight direction. Here, we propose a solution to these fundamental shortcomings by having robots learn to estimate distances to objects by their visual appearance. The learning process obtains supervised targets from a stability-based distance estimation approach. We have successfully implemented the process on a small flying robot. For the task of landing, it results in faster, smooth landings. For the task of obstacle avoidance, it results in higher success rates at higher flight speeds. Our results yield improved robotic visual navigation capabilities and lead to a novel hypothesis on insect intelligence: behaviours that were described as optical-flow-based and hardwired actually benefit from learning processes.
Ein Forschungsprojekt der Universität Siegen in Zusammenarbeit mit dem Institut für Mittelstandsforschung Bonn. Das Vorhaben "MINTdabei" — Stärkung der Selbst- und Fremdwahrnehmung von Young Women MINT Professionals (YWMP) beim Berufseinstieg und -aufstieg in berufliche Selbstständigkeit und Mittelstand" wurde mit Mitteln des Bundesministeriums für Bildung und Forschung (BMBF) unter dem Förderkennzeichen 01FP1620 gefördert.
Wir untersuchten Berufseinstieg und -aufstieg von YWMP in der beruflichen Selbstständigkeit und als Angestellte in mittelständischen Unternehmen, um durch die Identifikation spezifischer Probleme und Herausforderungen, insb. bei der Selbst- und Fremdwahrnehmung, Lösungsansätze für die Zukunft zu entwickeln. Ziel des Projektes ist es, damit einen kurz-, mittel- und langfristigen Beitrag zur Stärkung der Selbst- und Fremdwahrnehmung von Young Women MINT Professionals zu leisten.