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With the increasing capabilities of machine learning systems and their potential use in safety-critical systems, ensuring high-quality data is becoming increasingly important. In this paper, we present a novel approach for the assurance of data quality. For this purpose, the mathematical basics are first discussed and the approach is presented using multiple examples. This results in the detection of data points with potentially harmful properties for the use in safety-critical systems.
Camera-based object detection is widely used in safety-critical applications such as advanced driver assistance systems (ADAS) and autonomous vehicle research. Road infrastructure has been designed for human vision, so computer vision, with RGB cameras, is a vital source of semantic information from the environment. Sensors, such as LIDAR and RADAR, are also often utilized for these applications; however, cameras provide a higher spatial resolution and color information. The spatial frequency response (SFR), or sharpness of a camera, utilized in object detection systems must be sufficient to allow a detection algorithm to localize objects in the environment over its lifetime reliably. This study explores the relationship between object detection performance and SFR. Six state-of-the-art object detection models are evaluated with varying levels of lens defocus. A novel raw image dataset is created and utilized, containing pedestrians and cars over a range of distances up to 100-m from the sensor. Object detection performance for each defocused dataset is analyzed over a range of distances to determine the minimum SFR necessary in each case. Results show that the relationship between object detection performance and lens blur is much more complex than previous studies have found due to lens field curvature, chromatic aberration, and astigmatisms. We have found that smaller objects are disproportionately impacted by lens blur, and different object detection models have differing levels of robustness to lens blur
Sollen Forschungsleistungen gemessen und bewertet werden, stellen Publikationen eines der wichtigsten Kriterien dar. Die Bibliometrie liefert eine Vielzahl von (absoluten, relativen, normalisierten) Indikatoren, die Wissenschaftsmanager*innen für Leistungsträgeranalysen oder Forschungsevaluationen heranziehen können. Um valide Aussagen über wissenschaftliche Leistungen vornehmen zu können, müssen bibliometrische Kennzahlen mit anderen Leistungskriterien in Bezug gesetzt werden und es sind viele Faktoren sowie Umstände zu berücksichtigen. Auf diese wird in der vorliegenden Handreichung eingegangen. Sie sollen Wissenschaftsmanager*innen das Rüstzeug an die Hand geben, um bibliometrische Untersuchungen und deren Ergebnisse in dem jeweiligen Untersuchungsfall zielführend einordnen zu können.
Suffizienz als Ausweg?!
(2024)
The importance of high data quality is increasing with the growing impact and distribution of ML systems and big data. Also, the planned AI Act from the European commission defines challenging legal requirements for data quality especially for the market introduction of safety relevant ML systems. In this paper, we introduce a novel approach that supports the data quality assurance process of multiple data quality aspects. This approach enables the verification of quantitative data quality requirements. The concept and benefits are introduced and explained on small example data sets. How the method is applied is demonstrated on the well-known MNIST data set based an handwritten digits.
The healthcare sector's digital transformation necessitates the involvement of stakeholders through participation and co-creation processes. This study aims to investigate the understanding and implementation of participation and co-creation in the development of hybrid interaction technologies in healthcare. Eight interdisciplinary research projects were examined through semi-structured group interviews with 49 participants from academia, industry, and the application field. The interviews focused on participants' perspectives on project goals, user groups, access to the field, methods of participation and co-creation, and user motivation. The results highlight the diverse understandings of participation and co-creation, with some perceiving them as research-driven and others as already embedded in user- centered design. The projects emphasized user needs but often excluded stakeholders from collaborative decision-making. Challenges in achieving continuous involvement and co-decision were acknowledged. The findings underscore the need for reflexive practice and evaluation of participation and co-creation throughout the development process, as well as further research on participation across projects. By addressing these challenges and embracing participatory approaches, digital health applications can better address ethical concerns, build trust, and increase acceptance and adoption in the healthcare sector.
User-centered and Participatory Design approaches have become widespread within HCI, also when designing digital media for older adults. These methodologies are seen as crucial to adapt technology design to older people's needs and increase their acceptance of digital technology. Nevertheless, it is often difficult to reach a diverse group of older people, for instance, people with limited technology skills, limited mobility, or cognitive issues. In addition, gerontologists criticized lately how older people's participation unfolds in technology design projects, e.g. that people are pushed into the role of users. Little is known about the motivations and needs of older adults regarding their participation in HCI research. To close this gap, we conducted an online survey (N=46) and semi-structured interviews (N=8) focusing on motivations, willingness and experiences regarding participation. Results show that people are generally willing to participate due to interest in the topic, learning new things and social bonding. However, despite the conceptions within HCI that long-term engagement is crucial within participatory design, older people in the study preferred less commitment and more open formats.
Despite the higher uptake of digital media also in older age groups, there are still challenges for people of high ages and with cognitive or motoric problems, which prevent them from learning and using devices like smartphones or tablets. Tangible user interfaces provide an opportunity to connect these people to social media, thereby increasing their digital participation in society and reducing loneliness. In this paper, we discuss the challenges of intergenerational communication and research the opportunities affiliated with tangible technologies to overcome technology barriers for adults of high ages. We present a hybrid system for social media interactions between young smartphone users and their old relatives, who do not use mobile technologies. The system consists of a tangible user interface designed specifically for old adults that connects to a standard mobile messenger service. TAMI was designed in a user-centered process to fulfill the needs of older adults and tested in a longer-term field study with pairs of young and old relatives.
Rechtsextremismus
(2023)
Exilkroatische Gewalt in der Bundesrepublik Deutschland als transnationaler Rechtsterrorismus
(2023)
Rechtsterrorismus in der alten Bundesrepublik: Historische und sozialwissenschaftliche Perspektiven
(2023)
Zur Einführung
(2023)
The soundscape approach highlights the role of situational factors in sound evaluations; however, only a few studies have applied a multi‐domain approach including sound‐related, person‐related, and time‐varying situational variables. Therefore, we conducted a study based on the Experience Sampling Method to measure the relative contribution of a broad range of potentially relevant acoustic and non‐auditory variables in predicting indoor soundscape evaluations. Here we present the comprehensive dataset for which 105 participants reported temporally (rather) stable trait variables such as noise sensitivity, trait affect, and quality of life. They rated 6.594 situations regarding the soundscape standard dimensions, perceived loudness, and the saliency of its sound components and evaluated situational variables such as state affect, perceived control, activity, and location. To complement these subject‐centered data, we additionally crowdsourced object‐centered data by having participants make binaural measurements of each indoor soundscape at their homes using a low‐(self‐)noise recorder. These recordings were used to compute (psycho‐)acoustical indices such as the energetically averaged loudness level, the A‐weighted energetically averaged equivalent continuous sound pressure level, and the A‐weighted five‐percent exceedance level. This complex hierarchical data can be used to investigate time‐varying non‐auditory influences on sound perception and to develop soundscape indicators based on the binaural recordings to predict soundscape evaluations.
Datenlebenszyklus
(2023)
Ein Datenlebenszyklus dient als Rahmen für das strukturierte Datenmanagement. Er umfasst den gesamten Datenfluss von der Planung über die Erzeugung bis hin zur Aufbewahrung und Bereitstellung. An allen Stationen des Datenlebenszyklus können Maßnahmen für ein strukturiertes Datenmanagement getroffen werden, um Daten effizient zu nutzen, ihre Qualität sicherzustellen und ihre Langzeitverfügbarkeit zu gewährleisten.
Die vorliegende Grafik visualisiert den Datenlebenszyklus, der sich aus drei Hauptbereichen zusammensetzt: Planung und Nachnutzung, Erzeugung und Bearbeitung sowie Aufbewahrung und Bereitstellung. Jeder Bereich umfasst spezifische Aufgaben und Prozesse im Umgang mit Daten.
Die erste Phase „Planung und Nachnutzung“ beinhaltet zwei wesentliche Elemente. Als Erstes erfolgt die Planung des Forschungsvorhabens, bei der die Ziele, Methoden und Ressourcen definiert werden. Als Zweites umfasst sie die Recherche und Wiederverwendung bereits vorhandener Daten, um deren Nutzen und Potenzial für das vorliegende Projekt einzuschätzen.
Die zweite Phase „Erzeugung und Bearbeitung“ besteht aus drei Elementen, die in einem eigenen zirkulären Ablauf abgebildet sind. Als Erstes werden Daten erhoben und erfasst, entweder durch experimentelle Studien, Umfragen oder andere Methoden. Der Übergang von der ersten Phase zur zweiten Phase erfolgt über dieses Element, da hier die grundlegende Generierung eigener Daten innerhalb der Forschung beginnt. Als Zweites werden die gesammelten Daten gespeichert und organisiert, um ihre Integrität und Verfügbarkeit zu gewährleisten. Als Drittes erfolgt die Verarbeitung, Analyse und Auswahl der relevanten Informationen. Der Übergang von der zweiten Phase zur dritten Phase erfolgt aus diesem Element, da die gewonnenen Erkenntnisse für die weitere Aufbewahrung und Bereitstellung vorbereitet werden. Insgesamt bildet die zweite Phase einen kontinuierlichen Kreislauf.
Die dritte Phase „Aufbewahrung und Bereitstellung“ besteht aus drei Elementen. Als Erstes erfolgt die Publikation der Forschungsergebnisse, sei es in wissenschaftlichen Zeitschriften, Repositorien oder anderen relevanten Publikationsorten. Als Zweites werden die Daten archiviert, um ihre Langzeitverfügbarkeit und -integrität zu gewährleisten. Als Drittes wird Zugang zu den Forschungsergebnissen geschaffen, beispielsweise über eine gezielte Freigabe für bestimmte Nutzergruppen oder Erhöhung der Sichtbarkeit.
Forschungsdatenmanagement (FDM) nimmt in Wissenschaftsinstitutionen und Scientific Communities einen immer größeren Stellenwert ein. Hochschulen für angewandte Wissenschaften (HAW) sehen sich mithin der Aufgabe gegenübergestellt, Rahmenbedingungen für ein gelingendes FDM in Forschungsvorhaben zu schaffen. Die vorliegende Grafik hat zum Ziel, die Ausgestaltung dieser Rahmenbedingungen zu befördern, indem sie – mit Blick auf die operative Ebene – die Bedarfe der Forschenden mit FDM-Dienstleistungen zusammenbringt sowie Wechselwirkungen visualisiert. Auf diese Weise soll sie die Komplexität des Handlungsfelds FDM veranschaulichen und zugleich als Handreichung zur Ausgestaltung adäquater FDM-Ressourcen und -Prozesse für die Zielgruppe der Forschenden dienen.
Die Zusammenstellung basiert auf den generalisierten Erfahrungen, die zwischen 2020 und 2023 von den in der Förderlinie „FDMScouts.nrw“ finanzierten Projektverbünden in vier gemeinsamen Handlungsfeldern (Netzwerkarbeit, Information und Sensibilisierung, Koordination, Beratung) gesammelt wurden. Die zehn beteiligten Hochschulen arbeiteten in fünf Verbünden an Strukturen und Prozessen für eine nachhaltige Etablierung des Forschungsdatenmanagements vor Ort. Dabei berücksichtigt die Grafik überregionale Serviceangebote und Institutionen für den Bereich FDM, wie sie bis zum Zeitpunkt der Veröffentlichung zur Verfügung standen.
Beschäftigungs- und Arbeitsqualität von Berufen im Nonprofit-Sektor im Fokus sozialer Nachhaltigkeit
(2023)
Refractive power measurements serve as the primary quality standard in the automotive glazing industry. In the light of autonomous driving new optical metrics are becoming more and more popular for specifying optical quality requirements for the windshield. Nevertheless, the link between those quantities and the refractive power needs to be established in order to ensure a holistic requirement profile for the windshield. As a consequence, traceable high-resolution refractive power measurements are still required for the glass quality assessment. Standard measurement systems using Moiré patterns for refractive power monitoring in the automotive industry are highly resolution limited, wherefore they are insufficient for evaluating the camera window area. Consequently, there is a need for more sophisticated refractive power measurement systems that provide a higher spatial resolution. In addition, a calibration procedure has to be developed in order to guarantee for comparability of the measurement results. For increasing the resolution, a measurement setup based on an auto-correlation algorithm is tested in this paper. Furthermore, a calibration procedure is established by using a single reference lens with a nominal refractive power of 100 km-1. For the calibration of the entire measurement range of the system, the lens is tilted by an inclination angle orthogonal to the optical axis. The effective refractive power is then given by the Kerkhof model. By adopting the measurement and calibration procedure presented in this paper, glass suppliers in the automotive industry will be able to detect relevant manufacturing defects within the camera window area more accurately paving the way for a holistic quality assurance of the windshield for future advanced driver-assistance system (ADAS) functionalities. Concurrently, the traceability of the measurement results is ensured by establishing a calibration chain based on a single reference lens, which is traced back to international standards.
Abstract The modulation-transfer function (MTF) is a fundamental optical metric to measure the optical quality of an imaging system. In the automotive industry it is used to qualify camera systems for ADAS/AD. Each modern ADAS/AD system includes evaluation algorithms for environment perception and decision making that are based on AI/ML methods and neural networks. The performance of these AI algorithms is measured by established metrics like Average Precision (AP) or precision-recall-curves. In this article we research the robustness of the link between the optical quality metric and the AI performance metric. A series of numerical experiments were performed with object detection and instance segmentation algorithms (cars, pedestrians) evaluated on image databases with varying optical quality. We demonstrate with these that for strong optical aberrations a distinct performance loss is apparent, but that for subtle optical quality differences – as might arise during production tolerances – this link does not exhibit a satisfactory correlation. This calls into question how reliable the current industry practice is where a produced camera is tested end-of-line (EOL) with the MTF, and fixed MTF thresholds are used to qualify the performance of the camera-under-test.
Hintergrund: Durch die Digitalisierung hat sich die Art des Publizierens verändert. Es ergeben sich neue Publikationswege und -formen. Eine Reflexion der traditionellen Ansichten über Publikationen und die Sicherung der Qualität ist erforderlich. Damit ergibt sich die Intension der Arbeit: Gegenwärtige Qualitätskriterien zu erfassen, zu analysieren und neuartige Möglichkeiten aufzuzeigen.
Methoden: Die theoretische Basis für den Stand der Forschung erfolgt durch eine repräsentative Literaturrecherche. Die Extraktion der Qualitätskriterien basiert auf einer selektiven Quellenauswahl. Ergänzend werden sechs Expert:innen anhand eines halbstrukturiertem Interviewleitfadens befragt. Die extrahierten Erkenntnisse aus der Analyse fließen in einen Wissensgraph und liefern Ansätze für eine Qualitätssicherung. Die Modellierung einer Anwendung wird auf Basis des Standards BPMN 2.0 umgesetzt.
Ergebnisse: Es wird ein Qualitätskriterien-Index erstellt, der zur Ausweisung von Qualitätsmerkmalen für Publikationen führt. Diese bilden die Wissensbasis für eine Web-Anwendung. Der darin enthaltene prototypische Workflow leitet die:den Autor:in durch Kriterien. Als Ergebnis werden die Publikationen mit Qualitätsmerkmalen angereichert. Diese Arbeit liefert das theoretische Konzept für die Anwendung. Es beinhaltet ein Mockup und eine erste prototypische Umsetzung. Dies bietet die Basis für eine bedarfsorientierte, reale Entwicklung.
Schlussfolgerungen: Eine reale, technische Umsetzung ist mit entsprechenden Ressourcen realisierbar. Vorab wird empfohlen, die ermittelten Qualitätskriterien mit einer
Nutzer:innengruppe zu reflektieren bspw. in Form einer qualitativen Erhebung. Diese liefert Hypothesen und fördert die Akzeptanz für die Ausweisung von Qualität. Das Ergebnis behandelt keine fachdisziplin-spezifischen Aspekte. Erfolgt dies, wird es zu einer Erweiterung der Anwendung führen. Ebenfalls sollte die Usability der Anwendung getestet werden, bevor die reale Umsetzung erfolgt. Das erstellte Konzept, ein Mockup und der Prototyp liefern die Ausgangslage für die Entwicklung.
The importance of high data quality is increasing with the growing impact and distribution of ML systems and big data. Also the planned AI Act from the European commission defines challenging legal requirements for data quality especially for the market introduction of safety relevant ML systems. In this paper we introduce a novel approach that supports the data quality assurance process of multiple data quality aspects. This approach enables the verification of quantitative data quality requirements. The concept and benefits are introduced and explained on small example data sets. How the method is applied is demonstrated on the well known MNIST data set based an handwritten digits.
With the increasing capabilities of machine learning systems and their potential use in safety-critical systems, ensuring high-quality data is becoming increasingly important. In this paper we present a novel approach for the assurance of data quality. For this purpose, the mathematical basics are first discussed and the approach is presented using multiple examples. This results in the detection of data points with potentially harmful properties for the use in safety-critical systems.
Higher control engineering concepts, including artificial intelligence and model-based control, are recently becoming more popular in complex industrial applications because they enable a significant increase in efficiency. E.g., a model-based approach can be used to enhance the control and monitoring of several coupled components of a larger turbomachinery train. This requires dynamic models of the components, including all machine characteristics, which may experience a shift in their behavior over the course of their lifetime. Such changes occur due to natural fouling, wear of sub-components or external effects induced by maintenance measures. To overcome this problem, we model machine-characteristic maps with artificial neural networks, which may be used as part of prediction models in a model predictive control unit. If an appropriate data set is available, this allows us to adapt the model to the current behavior of the machine without requiring in-depth knowledge about the underlying physics of this “concept drift”, as it is known in literature. However, the training of neural networks is usually connected with high computational effort while the task needs to be executed in real-time during operation. Furthermore, in real operating conditions, machine sensors can only provide labeled data from the current operating point of the machine, which can be stationary for long operation periods of up to several months. In general, this yields only an unrepresentative data subset of the machine-characteristics, which is not sufficient to retrain the whole model to a new state. To solve these problems, we firstly reduce the model adaptation to a convex optimization problem, which can be efficiently solved in real-time conditions. Secondly, we use a specialized data management system with which we can integrate historical data to supplement the unrepresentative data subset. In this paper we show the application of the outlined method on a compressor map and discuss the advantages and requirements of the method in the context of modeling applications for industrial turbomachinery.
Process models in industrial applications, e.g. predictive maintenance or automation, are subject to both divergence from the underlying system due to their time-variant nature and to high complexity resulting from a wide operational range being covered. Hence, regression models require high accuracy for the present system state and at the same time need to be valid across the whole system operating space. While accuracy for the current system state can be gained by updating the model on the current data, the overall validity must often be retrieved from historical or design data. We propose a method to find an appropriate compromise for these two demands. A pre-trained artificial neural network (ANN) is continually updated on the current sensor data stream using convex optimisation. Thus, a unique and optimal solution is generated in each update step, while robust regression accuracy on the domain that is not covered by the arriving data subset is maintained. This is achieved by introducing a data management system to provide some historical data, constraining the optimisation problem and manipulating the architecture of the ANN. Models updated with this method show reasonable stability but display plastic behaviour at the current operating point.
A two-component system for control and monitoring of solar power towers with molten salt receivers is proposed. The control component consists of a model predictive control applica-tion (MPC) with a flexible objective function and on-line tunable weights, which runs on a In-dustrial PC and uses a reduced order dynamic model of the receiver’s thermal and flow dy-namics. The second component consists of a service-life monitoring unit, which estimates the service-life consumption of the absorber tubes depending on the current mode of operation based on thermal stresses and creep fatigue in the high temperature regime. The calculation of stresses is done based on a detailed finite element study, in which a digital twin of the re-ceiver was developed. By parallelising the model solver, the estimation of service-life con-sumption became capable of real-time operation. The system has been implemented at a test facility in Jülich, Germany, and awaits field experiments. In this paper, the modeling and archi-tecture are presented along simulation results, which were validated on a hardware-in-the-loop test bench. The MPC showed good disturbance rejection while respecting process variable constraints during the simulation studies.
Nachhaltigkeit als transdisziplinäre Herausforderung für Nonprofit-Organisationen – Eine Einführung
(2023)
A numerical study is carried out meticulously to scrutinize the impact of different shapes of chimneys like circular (outer dia, dc), convergent (outer dia, 0.5dc), divergent (outer dia, 1.5dc), sudden contraction (outer dia, 0.5dc), and sudden expansion (outer dia, 1.5dc) on the performance of an SCPP. Furthermore, the parametric impact with different chimney divergence angles (CDA, ϕ), and ground absorber slope angle (GSA, γ) on the SCPP performance is also scrutinized. Optimum divergence angle (ϕ=+0.75◦) enhances the power generation up to ~ 47% (76 kW) with a horizontal ground absorber surface. An increase or decrease in CDA lessens the power generation. With a sloped ground absorber angle γ=0.6◦, the gain in power generation is 60% (82 kW). The study of combination of ground sloped absorber (γ=0.6◦) and divergent chimney (ϕ=+0.75◦) shows enhancement of the power generation upto 80% (92 kW) more than the classical Manzaranes plant.
Der Chaos-Begriff ist für Pirandello nicht nur identitätsbestimmend, sondern wird auch mit seinem Novellenwerk in Verbindung gebracht, denn die ‚Novelle per un anno‘ scheinen sich jeder Bestimmung konkreter Ordnungsmuster zu widersetzen.
Die vorliegende Studie befasst sich mit der bisher noch nicht eingehend erforschten Frage danach, welche Strukturprinzipien den ‚Novelle per un anno‘ zugrunde liegen. Über klassisch-narratologische Textanalysen ausgewählter Novellen hinaus wird eine medienhistorische Perspektive eingenommen. Dies erlaubt Aussagen über den Einfluss des jeweiligen Publikationsmediums auf die Konstitution der Texte und die Gattung Novelle sowie eine Deutung der z.T. intensiven Umschriften der Novellen.
So zeigt sich, dass sich die Novellen innerhalb der Sammlung zueinander verhalten und über Themen, Motive und narrative Strukturen, aber auch über ihren medienhistorischen Kontext netzartig miteinander verbunden sind. Die Texte werden buchstäblich in die ‚Novelle per un anno‘ und damit einhergehend in eine Ästhetik des Chaos ‚eingeschrieben‘.