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Course of studies
Elevators contribute significantly to the electricity consumption of residential buildings, office buildings and commercial enterprises. In this paper, the electricity consumption is investigated using an elevator system and its individual operating states as example. In addition to analyzing and allocating the energy demand, this work examines how the individual operating states can be determined solely on the basis of the power consumption of the elevator. The knowledge gained from this, such as the usage behavior, the travel profile, or load, is determined independently of the elevator control system. A subsequent installation on any system can be easily realized. In this work, the investigated elevator requires a substantial part of the total annual power consumption in standby (>90 %). This shows an enormous potential for energy savings. The individual elevator states, as well as the load, can be detected very well on the basis of the measured total power consumption. The work thus shows exemplary the potential of an intelligent measurement system for the state detection of elevator systems.
In several domains of product design - like medical device design -
risk related use scenarios have to be analyzed in an early stage of design process.
Virtual reviews with users make it possible to get early insights in use problems.
Also, situations that are difficult to imitate in reality can be modeled and simulated
in virtual reality without risking the health of user. Therefore, virtual usability
tests are a promising approach which allow testing different scenarios under
controlled conditions. We chose a sample scenario from medical device design
and compare and evaluate different technical systems which can be used for virtual
usability tests. Aim is to derive guidance for virtual usability tests including
systems that can be used for specific conditions and the qualitative and quantitative
data, which can be collected with these systems. A formative test is performed
to evaluate and compare different systems. Also, a summative test is performed
to evaluate the selected systems. Results show that virtual usability tests
make it possible to test scenarios with users in an early stage and thus to encounter
possible interaction problems. But there are also many additional and new
things to consider compared to normal usability tests, such as checking motion
sickness, maintaining presence and the extensive operation of the technology.
Finally, a proposed method for virtual usability testing is described which also
comprises our equipment recommendations for virtual usability tests.
Operations within a Cyber Physical System (CPS) environment are naturally diverse and the resulting data sets include complex relations between sensors of the shopfloor devices setup, their configuration respectively. As Machine Learn- ing (ML) can increase the success of industrial plants in a variety of cases, like smart controlling, intrusion detection or predictive maintenance, clarifying responsibilities and operations for the whole lifecycle supports evaluating the potentially feasible scenarios. In this work, the need for highly configurable and flexible modules is demonstrated by depicting the complex possibilities of extending simple Machine Learning Operations (MLOps) pipelines with additional data sources, e.g., sensors. In addition to the particular modules core functionality, arbitrary evaluation logic or data structure specific anomaly detection can be integrated into the pipeline. With the creation of audit-trails for all operational modules, automated reports can be generated for increasing the accountability of the different physical devices and the data related processing. The concept is evaluated in the context of the project Collaborative Smart Contracting Platform for digital value-added Networks (KOSMoS), where a sensor is part of an ML pipeline and audit trails are realized using Blockchain (BC) technology.
Evolutionary strategy is increasingly used for optimization in various machine learning problems. It can scale very well, even to high dimensional problems, and its ability to globally self optimize in flexible ways provides new and exciting opportunities when combined with more recent machine learning methods. This paper describes a novel approach for the optimization of models with a data driven evolutionary strategy. The optimization can directly be applied as a preprocessing step and is therefore independent of the machine learning algorithm used. The experimental analysis of six different use cases show that, on average, better results are attained than without evolutionary strategy. Furthermore it is shown, that the best individual models are also achieved with the help of evolutionary strategy. The six different use cases were of different complexity which reinforces the idea that the approach is universal and not depending on specific use cases.
In this work, the comparability of the cooling effect of two Peltier elements from different manufacturers is investigated for cooling the reagent module of a chemiluminescence analyzer. The temperature inside the reagent module is measured and evaluated at several positions. In this study, two different types of verification tests are performed under extreme climatic conditions. On the one hand, in a specific functional “cold start test”, the temperature in the reagent module is measured and evaluated to determine whether the measured temperatures are within the specified temperature range after the specified time. In addition, the performance of the Peltier elements is also evaluated. On the other hand, as an unspecific regression stress test, a “smoke test” is performed that is mainly designed to allow identifying unpredictable events. While processing a long and
complex work list, any deviant system behavior can be detected. Again, the temperature inside the reagent module should not exceed the specified temperature range.
Parylene-C is a multifunctional polymer coating in the coating industry. In medical technology, it is approved for implants due to its biocompatibility. For example, it is used as a coating for electronic components and parts. The problem is that Parylene-C alone is too permeable to body water and the ions that are dissolved in it. Application as a coating material for long-term implants is therefore not possible. The infiltrating water not only corrodes the electronic components, but also reduces the adhesion between the Parylene-C and the coated surface. Therefore, layer systems of metal oxides and polymers are used for encapsulation. The aim of this work is to find out how different layer systems behave in relation to their water vapour transmission. Thicker systems should allow less water vapour to pass through than thinner ones. The task is to find this out using the test method for water vapour transmission barriers and to determine the water vapour transmission rate. It has been proven that in some cases the thicker layers performed worse than the thinner layer systems by a factor of ten. It has been shown that there is a relationship between the base substrate thickness, the thickness of the layer system and their flexibility.
Senatsausschuss Mobilität
(2022)
Ein Muss für jede Sifa
(2022)
Brennstoffzellen
(2022)
Cytokine Adsorber Use during DCD Heart Perfusion Counteracts Coronary Microvascular Dysfunction
(2022)
A simulation-based approach for measuring the performance of human-AI collaborative decisions
(2022)
Despite the widespread adoption of artificial intelligence and machine learning for decision-making in organizations, a wealth of research shows that situations that involve open-ended decisions (novel contexts without predefined rules) will continue to require humans in the loop. However, such collaboration that blends formal machine and bounded human rationality also amplify the risk of what is known as local rationality, which is when rational decisions in a local setting lead to globally dysfunctional behavior. Therefore, it becomes crucial, especially in a data-abundant environment that characterizes algorithmic decision-making, to devise means to assess performance holistically, not just for decision fragments. There is currently a lack of quantitative models that address this issue.
Despite the unabated growth of algorithmic decision-making in organizations, there is a growing consensus that numerous situations will continue to require humans in the loop. However, the blending of a formal machine and bounded human rationality also amplifies the risk of what is known as local rationality. Therefore, it is crucial, especially in a data-abundant environment that characterizes algorithmic decision-making, to devise means to assess performance holistically. In this paper, we propose a simulation-based model to address the current lack of research on quantifying algorithmic interventions in a broader organizational context. Our approach allows the combining of causal modeling and data science algorithms to represent decision settings involving a mix of machine and human rationality to measure performance. As a testbed, we consider the case of a fictitious company trying to improve its forecasting process with the help of a machine learning approach. The example demonstrates that a myopic assessment obscures problems that only a broader framing reveals. It highlights the value of a systems view since the effects of the interplay between human and algorithmic decisions can be largely unintuitive. Such a simulation-based approach can be an effective tool in efforts to delineate roles for humans and algorithms in hybrid contexts.
The importance of machine learning (ML) has been increasing dramatically for years. From assistance systems to production optimisation to healthcare support, almost every area of daily life and industry is coming into contact with machine learning. Besides all the benefits ML brings, the lack of transparency and difficulty in creating traceability pose major risks. While solutions exist to make the training of machine learning models more transparent, traceability is still a major challenge. Ensuring the identity of a model is another challenge, as unnoticed modification of a model is also a danger when using ML. This paper proposes to create an ML Birth Certificate and ML Family Tree secured by blockchain technology. Important information about training and changes to the model through retraining can be stored in a blockchain and accessed by any user to create more security and traceability about an ML model.
In diesem Vortrag werde ich auf die Programmierumgebungen (ROS) und Schnittstellen (keras/Tensorflow) eingehen, die es ermöglichen Roboter mit Hilfe von maschinellem Lernen zu trainieren. Dabei werde ich insbesondere die Möglichkeiten vorstellen, wie man einen Roboter in der Simulation (gazebo) trainieren kann, um die trainierten Modelle auf echte Roboter zu übertragen. Anhand von praktischen Beispielen mit mobilen Robotern und Greifarmen werden die Konzepte des Reinforcement Learnings, Active Learnings, Transfer Learnings und der Objekterkennung demonstriert. Das Testszenario besteht aus einem Holz-Labyrinth und einem Turtlebot Roboter, der mit Laser Range Scanner und einer 2D-Kamera ausgestattet ist. Dabei soll der Roboter lernen, autonom den Weg zur angegebenen Zielposition zu planen ohne dabei gegen ein Hindernis zu fahren. Es wird hierbei untersucht in wie weit die trainierten Modelle in leicht abgeänderten Szenarien funktionsfähig bleiben.
Unter dem Motto „Technologie bewegt Pflege“ werden Beiträge aus Wissenschaft, Praxis und Industrie präsentiert. In einem abwechslungsreichen Programm werden aus verschiedenen Blickwinkeln die unterschiedlichen Schwerpunkte im Themenfeld Pflege und Technik diskutiert. Die Beiträge auf der 5. Clusterkonferenz, ausgerichtet vom Pflegepraxiszentrum Freiburg, sind im vorliegenden Abstractband ausgeführt.
Arthrose – Prävalenz, Bedeutung und Implikationen für die Prävention und Gesundheitsförderung
(2022)
Sterben ist eines der großen Rätsel der Menschheit. Aus medizinischer Sicht handelt es sich dabei um ein sich schrittweise vollziehendes Organversagen. Die Psychologie betrachtet es als einen seelischen Verarbeitungsprozess. Sterben ist aber auch ein soziales Phänomen: Wir sprechen darüber, betrachten es auf Bildern, regulieren und organisieren es. Der sozialwissenschaftliche Blick auf das Sterben ist bisher nur wenigen bekannt. Die Beiträger*innen des Bandes zeigen theoretisch und empirisch die sozialen Ordnungen des Sterbens auf und eröffnen dabei neue Perspektiven zur Diskussion und Erforschung dieses besonderen Phänomens.
Gute und wirksame Führung setzt ein klares Führungsverständnis voraus. Das persönliche Führungsverständnis einer Führungskraft muss sich im Wesentlichen an den besonderen Bedingungen ihrer Führungsumwelt orientieren. Für die Entwicklung dieses richtigen Führungsverständnisses kann nur die Führungskraft selbst verantwortlich sein. Führungskräfte, die ihre Umwelt und ihre Rolle nicht reflektieren können, werden als Führungskraft kaum erfolgreich sein. Sie werden irgendwie führen, intuitiv, basierend auf ihrem Bauchgefühl. Das kann funktionieren. Für eine vertrauensvolle Führungskraft-Geführten- Beziehung wäre dies allerdings nachteilig. Dieses Buch liefert nicht nur theoretische Grundlagen, sondern auch praktische Hilfestellungen, die sich über viele Jahre hinweg in der Praxis bewährt haben. Mithilfe dieses Buches lernen Führungskräfte, ihre Führungsumwelt zu verstehen und darauf aufbauend ihr Führungsverständnis zu entwickeln. Weiterhin wird gezeigt, wie sie ihr Führungsverständnis vermitteln und danach handeln können. Insofern wird in diesem Buch auf die Darstellung eines normativen, idealen und all- gemeingültigen Ansatzes bewusst verzichtet. Darin unterscheidet sich dieses Buch von vielen anderen Werken, die ein einziges Führungsideal propagieren.
Gesundheitsökonomie
(2022)
Background: Adolescence is a phase of higher vulnerability for suicidal behavior. In Germany, almost 500 adolescents and young adults aged 15-25 years commit suicide each year. Youths in rural areas are characterized by a higher likelihood of poorer mental health. In rural areas, appropriate support for adolescents and young adults in mental health crises is difficult to access. The general acceptability of digital communication in youths can make the provision of an eHealth tool a promising strategy.
Objective: The aim of this study was to explore the health needs regarding suicide prevention for adolescents and young adults in rural areas of Germany and Switzerland and to identify characteristics of suitable e-mental health interventions.
Methods: This study reports on a qualitative secondary analysis of archived data, which had been collected through formative participatory research. Using 32 semistructured interviews (individually or in groups of 2) with 13 adolescents and young adults (aged 18-25 years) and 23 experts from relevant fields, we applied a deductive-inductive methodological approach and used qualitative content analyses according to Kuckartz (2016).
Results: Experts as well as adolescents and young adults have reported health needs in digital suicide prevention. The health needs for rural adolescents and young adults in crises were characterized by several categories. First, the need for suicide prevention in general was highlighted. Additionally, the need for a peer concept and web-based suicide prevention were stressed. The factors influencing the acceptability of a peer-driven, web-based support were related to low-threshold access, lifelike intervention, anonymity, and trustworthiness.
Conclusions: The results suggest a need for suicide prevention services for adolescents and young adults in this rural setting. Peer-driven and web-based suicide prevention services may add an important element of support during crises. By establishing such a service, an improvement in mental health support and well-being could be enabled. These services should be developed with the participation of the target group, taking anonymity, trustworthiness, and low-threshold access into account.
Die komplexen Herausforderungen in der Gesundheitsversorgung erfordern die Zusammenarbeit verschiedener Berufsgruppen.
Den Grundstein dafür legen interprofessionelle Ausbildungsinhalte. Die erforderlichen Kompetenzen können durch unterschiedlichedidaktische Zugänge sowie Lehr- und Lernmethoden angebahnt werden. Das vorliegende narrative Review stellt die didaktische und methodische Realisierbarkeit interprofessioneller Ausbildungsinhalte zur Verbesserung der interprofessionellen Kompetenz in den Gesundheitsberufen dar. Ergänzend wird die Evaluation der Lehr- und Lernmethoden berücksichtigt. Der Artikel stellt die Ergebnisse vor und diskutiert diese vor dem Hintergrund bisheriger Erkenntnisse.
As planetary health education enters medical and health professional training, transversal implementation across curricula is critical in developing its full potential and enabling future health professionals to meet the social, environmental, and health challenges of current and future generations in an integrated manner. To advance the transversal implementation of planetary health education, our study proceeded through: (1) a sequence analysis of documents framing physiotherapy education to identify relevant nexus points; (2) an explorative implementation of planetary health into foundational anatomy and physiology modules identified as critical nexus points; (3) practical implementation during the 2021 autumn semester. Implementation in the operative foundations of healthcare education—anatomy and physiology—enables the emphasis of the ecological nature of human bodies and interconnection with our planetary environment. Musculoskeletal joints accentuate the relational nature of bodies highlighted across current research and traditional knowledges, as dynamically pervaded and in interaction with culture, technology, objects, ideas, plants, planets, etc. Teaching relational anatomies thus highlights planetary health as the transversal foundation of medical and healthcare education. Making this foundation more explicit will be critical for the transversal implementation of planetary health education and subsequent practice, as well as the fundamental shifts in our understanding of human lives and health they require.
For all hardware companies, telemetry is the key to growing services profitably with digitally-enabled services and optimizing the total cost to serve.
Yet, the TSIA Field Services Benchmark data also shows that building this foundation remains difficult. The key to providing telemetry at scale is to understand and communicate the value of telemetry in two ways—internally, to get the resources to drive it, and externally to customers, to convince them to adopt and consume the telemetry offers that will drive their business outcomes.
In this paper, Harald Kopp and Kevin Bowers give guidance and key insights on how to present the value of telemetry to customers and internal stakeholders.
Algorithmic Music Generation
(2022)
Zunehmend werden Tätigkeiten wie die Konzeption, die Herstellung und Zusammenstellung von Medienprodukten, die früher durch menschliche Arbeitsleistungen, professionelle Gestaltungskompetenz und Kreativität geprägt waren, durch automatisierte und intelligente Routinen und Programme übernommen. Wie dies bei Games, Kinofilmen, Streaming, Musik, belletristischer Literatur und Mangas geschieht und welche Folgen dies hat, dokumentiert nun das Buch „KI in der digitalisierten Medienwirtschaft“.
In this work, we characterise a flexural mechanical amplifier, which is used for the realisation of a miniaturised piezoelectric inchworm motor designed for large force (some N) and stroke (tens of mm) operation as it is required e.g., for medical implants. The characterisation is based on high precision optical displacement measurements and a force self-sensing approach. An optically measured displacement of 292 nm in lateral direction and 910 nm in vertical direction of the flexural mechanical amplifier has been obtained, corresponding to a deflection attenuation factor of 3.1. Piezoelectric self-sensing of force was used to determine a force amplification factor of 3.43 from the mechanical oval structure.
Die klinische Leistungsfähigkeit von Medizinprodukten rückt bei den Anforderungen moderner Entwicklungsprozesse und den damit verbundenen Regularien immer stärker in den Vordergrund. Die Nachweise für diese Performance können jedoch oft erst sehr spät im Rahmen klinischer Prüfungen bzw. Studien erreicht werden. Ein Lösungsansatz für dieses Problem können virtuellen klinischen Studien darstellen, die auf Simulationsmethoden aufbauen und so helfen, frühzeitig wichtige Weichen in der Entwicklung zu stellen und verschiedene konzeptionelle Ansätze für die Produktentwicklung sowie eine Optimierung spezieller Parameter zu erreichen. Die Nutzung derartiger Techniken wird sowohl durch die Europäisch Kommission im Abschlussreport der Avicenna Alliance als auch gezielt von der FDA im Rahmen verschiedener Guidance-Dokumente vorgestellt und forciert. Das Medical Solution Center-BW greift diese Ansätze auf und strebt an, ein Netzwerk aus Partnern aus Industrie und Wissenschaft aufzubauen, dass die Nutzung von Simulation / HPC im Rahmen der Entwicklung von Medizinprodukten systematisch zu erschließen. Das betrifft insbesondere die Option zur Entwicklung virtueller klinischer Studien in den Bereichen der strukturmechanischen Simulation von Knochen-Implantat-Systemen sowie der strömungsmechanischen Simulation im Bereich der endovaskulären Chirurgie. In unserem Beitrag werden wir einen prinzipiellen Vorschlag zur Implementierung eines Verfahrens vorstellen, welches die Bewertung von Medizinprodukten mit Hilfe biomechanischer Simulationen in virtuellen klinischen Studien ermöglicht und explizite Simulationsanwendungen aus dem Bereich der Knochen-Implantat-Systeme präsentieren.
Von Robotern, die in der Industrie 4.0 zusammenarbeiten, über intelligente Sprachassistenten bis zu autonom fahrenden Autos – Künstliche Intelligenz verändert unsere Wirtschaft und Gesellschaft nachhaltig. Die selbstlernenden und sich fortlaufend verbessernden KI-Systeme ermöglichen effizientere Abläufe in Produktion und anderen Bereichen. Vollkommen neue Geschäftsmodelle können durch sie entstehen. Die Möglichkeiten sind grenzenlos – und doch sollte sich eine so einflussreiche Technologie innerhalb bestimmter Grenzen bewegen, damit sie uns tatsächlich hilft. Eine zuverlässige, funktionale und vor allem sichere KI braucht gewisse Regeln: zunächst ein gemeinsames Verständnis und eine einheitliche Sprache, sodass alle vom Gleichen reden. Außerdem sind offene Schnittstellen nötig, damit die Systeme ihr volles Potenzial ausschöpfen und effizient zusammenarbeiten. Nur so können verschiedene KI-gesteuerte Maschinen miteinander kommunizieren, werden Produkte entlang der gesamten Wertschöpfungskette sichtbar. Gleichzeitig spielen ethische Fragen eine zentrale Rolle beim Einsatz Künstlicher Intelligenz. Verzerrung, Diskriminierung und Manipulation sollten von vornherein verhindert werden, wenn KI dem Menschen nutzen soll.
Bei all diesen Aspekten leisten Normen und Standards einen zentralen Beitrag: Sie definieren Anforderungen an Künstliche Intelligenz und strukturieren die Technologielandschaft. Damit sind sie ein strategisch wichtiges Instrument zur Stärkung der Innovations- und Wettbewerbsfähigkeit der deutschen Wirtschaft. Der geschätzte wirtschaftliche Nutzen von Normen beträgt rund 17 Milliarden Euro im Jahr. Nicht zuletzt deshalb fiel jetzt der Startschuss für die Arbeiten an der zweiten Ausgabe der Normungsroadmap Künstliche Intelligenz. Die Aufgabe der vorliegenden Roadmap ist es, einen strategischen Fahrplan für die KI-Normung zu formulieren.
The Sustainable Development Goals (SDGs) of the United Nations focus on key issues for the transformation of our world towards sustainability. We argue for stronger integration of the SDGs into requirements and software engineering and for the creation of methods and tools that support the analysis of potential effects of software systems on sustainability in general and on SDGs in particular. To demonstrate one way of undertaking this integration, we report on how the Sustainability Awareness Framework (SusAF -- a tool developed by the authors of this paper) can be mapped to the SDGs, allowing the identification of potential effects of software systems on sustainability and on the SDGs. This mapping exercise demonstrates that it is possible for requirements engineers working on a specific system to consider that system's impact with respect to SDGs.
Context: The Software Engineering process can be seen as a socio-technical activity that involves fulfilling one's role as part of a team. Accordingly, software products and services are the result of a specific collaboration between employees (and other stakeholders). In recent years, sustainability, which Requirements Engineers often paraphrase as the ability of a system to endure, is becoming part of the process and thus the responsibility of Software Engineers (SE) as well. Objectives: This study shines the spotlight on the role of the SE: their self-attribution and their awareness for sustainability. We interviewed 13 SEs to figure out how they perceive their own role and to which extent they implement the topic of sustainability in their daily work. By visualizing these two sides, it is possible to debate changes and their possible paths to benefit the Software Engineering process including sustainability design. Results: A discrepancy between the current role and the ideal role of SEs becomes visible. It is characterized in particular by dwelling on their “classic” or time-honored tasks as an executive force, such as coding. At the same time, they point out the still missing necessity of an interdisciplinary, from communication coined working method. According to our interviewees SEs are inefficiently involved in the design process. They do not sufficiently assume their responsibility for the software and its sustainability impacts.
Software engineering, as a central practice of digitalization, needs to become accountable for sustainability. In light of the ecological crises and the tremendous impact of digital systems on reshaping economic and social arrangements - often with negative side-effects - we need a sustainability transformation of the digital transformation. However, this is a complex and long-term task. In this article we combine an analysis of accountability arrangements in software engineering and a model of sustainability transformations to trace how certain dynamics are starting to make software engineering accountable for sustainability in the technological, cultural, economic and governance domains. The article discusses existing approaches for sustainable software engineering and software engineering for sustainability, traces emerging discourses that connect digitalization and sustainability, highlights new digital business models that may support sustainability and shows governance efforts to highlight “green and digital” policy problems. Yet, we argue that these are so far niche dynamics and that a sustainability transformation requires a collective and long-lasting effort to engender systemic changes. The goal should be to create varied accountability arrangements for sustainability in software engineering which is embedded in complex ways in society and economy.