Future mobility will be highly automated, multimodal, and ubiquitous and thus have the potential to address a broader range of users. Yet non-average users with special needs are often underrep-resented or simply not thought of in design processes of vehicles and mobility services, leading to exclusion from standard transportation. In consequence, it is crucial for designers of such vehicles and services to consider the needs of non-average users from the begin on. In this paper, we present a design framework that helps designers taking the perspective and thinking of the needs of non-average users. We present a set of exemplary applications from the literature and interviews and show how they fit into the framework, indicating room for further developments. We further demonstrate how the framework supports in designing a mobility service in a fictional design process. Overall, our work contributes to universal design of future mobility.
One of the main goals of driving assistant systems is to prevent road accidents. However, if an accident has happened, system support is comparably sparse. In this paper, we, therefore, focus on the period after an accident has happened and conduct interviews (N = 7) with experienced rescue workers. We provide insights into the rescue process and initial design requirements, as well as a classification of potential post-accident systems' roles (accident scout, virtual first responder, virtual first aid partner, chronologist). Overall, an extension of post-accident assistant systems could be a meaningful step to improving future road safety concepts.
Derzeit gibt es in Deutschland rund 7,9 Mio. Menschen mit körperlichen Behinderungen. Rund 18,1 Mio. Menschen in Deutschland sind älter als 60 Jahre. Ein Großteil dieser Menschen sind nicht mehr in der Lage selbstständig Auto zu fahren und sind daher nicht mobil und abhängig von anderen. Ein Arztbesuch, das Besuchen der Familie und Freunde, sowie alltägliche Dinge, wie zum Beispiel einkaufen gehen, sind oft durch körperliche Einschränkungen nicht mehr möglich.
Ein Anliegen beim Schreiben dieses Buches war es, die Darstellung so weit wie möglich in sich abgeschlossen zu halten, damit es nicht nötig ist, weitere Lehrbücher zu benutzen, um sich den Lernstoff zu erarbeiten. Obwohl wir hoffen, dass uns dies weitgehend gelungen ist, sind wir bei den mathematischen und wahrscheinlichkeitstheoretischen Grundlagen an gewisse Grenzen gestoßen.
The transformation of the power grid towards higher shares of power electronics requires more power quality (PQ) measurements. Since the dynamic of the measured signals is increasing, shorter measurement windows are required to correctly assess the spectral PQ. When it comes to spectral analysis using the discrete Fourier transform (DFT), the phase information on a DFT-bin is quite sensitive towards distortions such as spectral leakage, especially when the measurement windows are shortened further. One approach of decreasing the errors induced by spectral leakage is mains frequency synchronous sampling. As a consequence, the phase information contains more useful information and could be used in further analysis. However, it must be checked if this information is in fact useful. In this paper, a novel quality index is introduced that indicates the change of phase at a DFT-bin over time in consecutively computed spectra. This index is extensively validated with regard to disturbances such as non-synchronicity and noise. Thereafter, a measurement example is given where the quality index is applied.
This study investigates whether employees' psychological ownership results in stewardship behavior and whether this relationship is affected by an employee's perception of the organization's agency culture. A survey of the financial managers of 129 firms in Germany generally confirms these expectations. In addition, and surprisingly, our findings suggest a negligible effect of an agency culture on the relationship between psychological ownership and stewardship behavior when managers perceive high psychological ownership. Thereby, our study enriches the literature on the consequences of psychological ownership by providing insights into the boundary conditions of such outcomes at the manager level.
The present work uses a user-centered design approach to investigate potential design requirements and user scenarios of social robots in municipal services. Qualitative interviews paired with two interactive workshops compared the expectations of potential costumers with those of administration experts of municipalities. The results indicate mainly similar expectations of the robot’s design and functionality, but revealed different perspectives: Customers thought more about specific design characteristics (e.g. the robots body temperature), while administration experts reflected more on service aspects (e.g. adapting the needs of different customers and especially people in need of support or the robustness of the system). Moreover, precise user scenarios that integrate the different ideas and preferences are presented. These can help researchers and practitioners to extract design requirements and application scenarios that are considered by the different stakeholders.
Stereotypes and scripts guide human perception and expectations in everyday life. Research has found that a robot’s appearance influences the perceived fit in different application domains (e.g. industrial or social) and that the role a robot is presented in predicts its perceived personality. However, it is unclear how the surroundings as such can elicit a halo effect leading to stereotypical perceptions. This paper presents the results of an experimental study in which 206 participants saw 8 cartoon pictures of the robot Pepper in different application domains in a within-subjects online study. Results indicate that the environment a robot is placed in has an effect on the users’ evaluation of the robot’s warmth, competence, status in society, competition, anthropomorphism, and morality. As the first impression has an effect on users’ expectations and evaluation of the robot and the interaction with it, the effect of the application scenarios has to be considered carefully.
While the usage of digital systems in the medical sector has increased, nursing activities are still mostly performed without any form of digital assistance. Considering the complex and demanding procedures the medical personnel is confronted with, a high task load is expected which is prone to human errors. Solutions, however, need to match staff requirements and ideally involve them in the development process to ensure acceptance and usage. Based on desired application scenarios, we introduce a concept of an augmented reality (AR)-based patient data application that provides context-relevant information for nursing staff and doctors. Developed for the Hololens 2, the application allows the retrieval and synchronization of the patient data from the host network of the respective hospital information system. For this purpose, a system infrastructure consisting of several software components was developed to simulate the exchange between the AR device and the independent hospital environment. The paper outlines the conceptual approach based on requirements collected from nurses, related work, the technical implementation and discusses limitations and future developments.
The nursing profession is becoming increasingly complex: administrative and nursing tasks have to be performed in parallel, under time pressure and in shifts. These stressful working conditions also affect safety-critical processes such as the correct dispensing of medication. As digitization continues, new technologies such as augmented reality (AR) glasses are emerging that offer potential solutions. However, a practical implementation requires a deep understanding of the underlying problem and user needs. The aim of this paper is to first, discover pains and gains in the process of medication dispensation and second, develop a conceptual prototype for AR glasses as a basis for discussion on the applicability in practice. A participatory design process with nursing professionals and experts from technical and organizational fields was established. As result, we present a conceptual prototype, that (A) respects the context of use, (B) guides users while dispensing medication according to prescription, (C) displays useful information about medical preparations, procurement of alternate medicine and dosage variations and (D) uses checklists and error recognition to increase safety. Multidisciplinary feedback workshops indicate an overall positive resonance. We advise paying attention to the spatial and economic situation while using AR as a support tool providing flexibility for users.
Internet of things (IoT) devices increasingly permeate everyday life and provide vital and convenient information. Augmented reality (AR) enables the embedding of this information in the environment using visualizations that can contextualize data for various applications such as Smart Home. Current applications providing a visual representation of the information are often limited to graphs or bar charts, neglecting the variety of possible coherence between the subject and the visualization. We present a setup for real-time AR-based visualizations of data collected by IoT devices. Three distinct battery-powered IoT microcontroller systems were designed and programmed. Each is outfitted with numerous sensors, i.e. for humidity or temperature, to interact with the developed AR application through a network connection. The AR application was developed using Unity3D and the Vuforia AR SDK for Android-based mobile devices with the goal of providing processed and visualized information that is comprehensible for the respective context. Inspired by weather applications for mobile devices, the visualization contains animated dioramas, with changing attributes based on the input data from the IoT microcontroller. This work contains the configuration of the IoT microcontroller hardware, the network interface used, the development process of the AR application, and its usage, complemented by possible future extensions described in an outlook.
Deployment of modern data-driven machine learning methods, most often realized by deep neural networks (DNNs), in safety-critical applications such as health care, industrial plant control, or autonomous driving is highly challenging due to numerous model-inherent shortcomings. These shortcomings are diverse and range from a lack of generalization over insufficient interpretability and implausible predictions to directed attacks by means of malicious inputs. Cyber-physical systems employing DNNs are therefore likely to suffer from so-called safety concerns, properties that preclude their deployment as no argument or experimental setup can help to assess the remaining risk. In recent years, an abundance of state-of-the-art techniques aiming to address these safety concerns has emerged. This chapter provides a structured and broad overview of them. We first identify categories of insufficiencies to then describe research activities aiming at their detection, quantification, or mitigation. Our work addresses machine learning experts and safety engineers alike: The former ones might profit from the broad range of machine learning topics covered and discussions on limitations of recent methods. The latter ones might gain insights into the specifics of modern machine learning methods. We hope that this contribution fuels discussions on desiderata for machine learning systems and strategies on how to help to advance existing approaches accordingly.
In this study, we looked at the competencies and changes in the competency spectrum required for global start-ups in the digital age. Specifically, we explored intergenerational collaboration as an intervention in which experienced business-people from senior adult groups support young entrepreneurs. We conducted a Delphi study with 20 experts from different disciplines, considering the study context. The results of this study shed light on understanding the necessary competencies of entrepreneurs for intergenerationally supported start-up innovation by providing 27 competencies categorized as follows: intergenerational safety facilitation, cultural awareness, virtues for growth, effectual creativity, technical expertise, responsive teamwork, values-based organization, and sustainable network development. In addition, the study results also reveal the competency priorities and the minimum requirements for each competency group based on the global innovation process and can be used to develop a readiness assessment for start-up entrepreneurs.
The safekeeping of the electromagnetic compatibility (EMC) by reducing the electromagnetic interferences (EMI) of power electronic is extremely important. In this contribution, the application of a frequency variable resonant inverter for powertrain applications is simulatively investigated. First, the advantage of resonant switching patterns compared to pulse width modulation schemes is outlined. Next, the characteristics of a frequency variable resonant tank are discussed. Including the electrical stator model of a brushless DC (BLDC) motor, the interdependencies between a running BLDC and the resonant tank are analyzed. A model based resonant operation of an exemplarily parametrized BLDC is carried out. The contribution is closed by a summary and outlook.
Diseases such as cancer are often defined by dysregulation of gene expression. Noncoding RNAs (ncRNA) such as microRNAs are involved in gene expression and cell-cell communication. Many other ncRNAs exist, such as circular RNAs and small nucleolar RNAs. A wealth of knowledge is available for many ncRNAs, but the information is federated in many databases. A small number of highly complementary ncRNA databases are discussed in this work. Their relevance for cancer research is highlighted, and some of the current problems and limitations are revealed. A central or shared database enforcing community reporting and quality standards is needed in the future. • RNA-seq • Noncoding RNAs • Databases • Data repositories Conclusion The study's outcome recommends that p. ginseng could be an effective agent for preventing the PA and inflammation during the post-operative stage.
Our goal is to examine the efficiency of different intraday electricity markets and if any of their price prediction models are more accurate than others. This paper includes a comprehensive review of Germany, France, and Norway’s (NOR1) day-ahead and intraday electricity market prices. These markets represent different energy mixes which would allow us to analyze the impact of the energy mix on the efficiencies of these markets. To draw conclusions about extreme market conditions, (i) we reviewed the market data linked to COVID-19. We expected higher volatility in the lockdowns than before and therefore decrease in the efficiency of the prediction models. With our analysis, (ii) we want to draw conclusions as to whether a mix based mainly on renewable energies such as that in Norway implies lower volatilities even in times of crisis. This would answer (iii) whether a market with an energy mix like Norway is more efficient in highly volatile phases. For the analysis, we use data visualization and statistical models as well as sample and out-of-sample data. Our finding was that while the different price and volatility levels occurred, the direction of the market was similar. We could find evidence that our expectations (i–iii) were met.
Technology assessment (TA) occurs in a variety of educational contexts, its content and methods can contribute to dealing with socially relevant issues from different perspectives across disciplinary boundaries. However, the transdisciplinarity of TA raises the question in which educational contexts TA perspectives are introduced and how educational processes can be effectively structured and strengthened. This issue therefore addresses both perspectives: practice in various trans- and interdisciplinary educational contexts, as well as TA’s own educational practice.
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