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Deep brain stimulation (DBS) is an established therapy for movement disorders such as in Parkinson's disease (PD) and essential tremor (ET). Adjusting the stimulation parameters, however, is a labour-intensive process and often requires several patient visits. Physicians prefer objective tools to improve (or maintain) the performance in DBS. Wearable motion sensors (WMS) are able to detect some manifestations of pathological signs, such as tremor in PD. However, the interpretation of sensor data is often highly technical and methods to visualise tremor data of patients undergoing DBS in a clinical setting are lacking. This work aims to visualise the dynamics of tremor responses to DBS parameter changes with WMS while patients performing clinical hand movements. To this end, we attended DBS programming sessions of two patients with the aim to visualise certain aspects of the clinical examination. PD tremor and ET were effectively quantified by acceleration amplitude and frequency. Tremor dynamics were analysed and visualised based on setpoints, movement transitions and stability aspects. These methods have not yet been employed and examples demonstrate how tremor dynamics can be visualised with simple analysis techniques. We therefore provide a base for future research work on visualisation tools in order to assist clinicians who frequently encounter patients for DBS therapy. This could lead to benefits in terms of enhanced evaluation of treatment efficacy in the future.
This paper presents a feasibility study for the production of recycled glycol modified polyethylene terephthalate (PETG) material for additive manufacturing. Past studies showed a variety of results for the recycling of 3D-printing material, therefore the precise effect on the material properties is not completely clear. For this work, PETG waste of the same grade was recycled once and further processed into 3D printing filament. The study compares three blend ratios between purchased plastic pellets and recycled pellets to determine the degradation effect of one recycling cycle and possible blend ratios to counter these effects. Furthermore, the results include a commercially available filament. The comparison uses the filament diameter, the dimensional accuracy of the printed test specimen and mechanical properties as quality criteria. The study shows that the recycled material has a minor decrease concerning the tensile strength and Young’s modulus.
The following paper aims to find out consumers' expectations and attitudes towards the innovation "Metaverse". It will also be explored which role the Meta Group plays in mass adaption and how the company influences consumers' possible use and opinion on the project. These results are connected to the fashion industry, further exploring new types of products and a possible distribution channel. Therefore, this study is useful to developers of Metaverses and AR/VR products, the Meta Group, and fashion companies. The main results of this research are: Meta and the Metaverse are seen as critical, the required technology has not yet reached mainstream use, but interest is present. Digital fashion had participants divided, some not willing to spend any money and some already having spent over 100€, although the Metaverse's influence on future purchases is little. The Metaverse could serve as a new distribution channel for clothing products. To conduct this research Google Forms was used. The research is classified as survey-based. The biggest limitation is the nonexistence of the Metaverse as envisioned by Meta, making it hard for participants to answer some of the questions asked.
Electric drive systems are increasingly used in automobiles. However, the combination of comfort, dynamics and safety requirements places high demands on the torque accuracy. The complex interplay of battery, inverter and electrical machine causes a lot of system uncertainties based on parameter fluctuations and measurement errors that influence the system performance. In this paper these influences on the closed loop torque control are analyzed and quantified using a variance based sensitivity analysis. The method enables to connect the variance of the torque accuracy with the parameter uncertainties causing this variance. Moreover, it quantifies the influences of the parameters independent of the complexity of the analyzed system. In addition, two methods to ensure convergence of the estimated variance based sensitivity measures are proposed. The results of the analysis are presented for 19 static working points of an battery electric drive system.
Unternehmen verlassen sich bei der Entwicklung von Software und Lösungen häufig auf das Know-How externer Dienstleister. Moderne Arbeits- und Kollaborationsformen verändern gleichzeitig die Entwicklung von Produkten und Dienstleistungen. Wie beeinflussen diese Trends die Zusammenarbeit und Kooperation zwischen Unternehmen und ihren externen agilen Dienstleistern? Ziel dieser wissenschaftlichen Arbeit ist es herauszufinden, welche Schritte unternehmen müssen, um agiles Arbeiten und die Zusammenarbeit mit externen Dienstleistern umzusetzen. Daher wurde anhand einer Fallstudie inklusive einer qualitativen Befragung herausgefunden und aufgezeigt, welche Maßnahmen und Handlungen Unternehmen ergreifen müssen, um das Ziel einer effektiven Umsetzung einer agilen Zusammenarbeit und Kooperation zu erreichen. Drei Kernthemen wurden identifiziert, auf deren Grundlage die Forschungsfragen zu den Maßnahmen beantwortet werden: Erstens, welche Möglichkeiten Unternehmen haben, ein internes agiles Setup zu implementieren, um mit agilen Dienstleistern auf Augenhöhe zusammenzuarbeiten. Zweitens, welche Vertragsvarianten die agile Zusammenarbeit unterstützen und verbessern können und drittens, welche agilen Techniken und Methoden in der agilen Zusammenarbeit eingesetzt werden sollten. Die Ergebnisse der Fallstudien bestätigen die Annahme, dass die drei identifizierten Kernthemen für eine effektive Zusammenarbeit im agilen Umfeld essenziell sind. Während einerseits nachgewiesen wurde, dass sich die Vertragsanforderungen hinsichtlich ihrer Flexibilität und Anpassungsfähigkeit veränderten, wurde andererseits auch nachgewiesen, dass das interne Setup agile Treiber, Techniken und Methoden erfordert, um eine effektive Zusammenarbeit mit agilen Dienstleistern zu ermöglichen. Dieser Artikel gibt einen Überblick über die wichtigsten Inhalte innerhalb der drei genannten Kernthemen und gibt Unternehmen zudem Hinweise, wie sie eine Basis für eine effektive Zusammenarbeit schaffen können.
Unintended nuclear war
(2021)
While the contribution of renewable energy technologies to the energy system is increasing, so is its level of complexity. In addition to new types of consumer systems, the future system will be characterized by volatile generation plants that will require storage technologies. Furthermore, a solid interconnected system that enables the transit of electrical energy can reduce the need for generation and storage systems. Therefore, appropriate methods are needed to analyze energy production and consumption interactions within different system constellations. Energy system models can help to understand and build these future energy systems. However, although various energy models already exist, none of them can cover all issues related to integrating renewable energy systems. The existing research gap is also reflected in the fact that current models cannot model the entire energy system for very high shares of renewable energies with high temporal resolution (15 min or 1-h steps) and high spatial resolution. Additionally, the low availability of open-source energy models leads to a lack of transparency about exactly how they work. To close this gap, the sector-coupled energy model (UCB-SEnMod) was developed. Its unique features are the modular structure, high flexibility, and applicability, enabling it to model any system constellation and can be easily extended with new functions due to its software design. Due to the software architecture, it is possible to map individual buildings or companies and regions, or even countries. In addition, we plan to make the energy model UCB-SEnMod available as an open-source framework to enable users to understand the functionality and configuration options more easily. This paper presents the methodology of the UCB-SEnMod model. The main components of the model are described in detail, i.e., the energy generation systems, the consumption components in the electricity, heat, and transport sectors, and the possibilities of load balancing.
In this paper two simple synthetic aperture radar (SAR) methods are applied on data from a 24 GHz FMCW radar implemented on a linear drive for educational purposes. The data of near and far range measurements are evaluated using two different SAR signal processing algorithms featuring 2D-FFT and frequency back projection (FBP) method (Moreira et al., 2013). A comparison of these two algorithms is performed concerning runtime, image pixel size, azimuth and range resolution. The far range measurements are executed in a range of 60 to 135 m by monitoring cars in a parking lot. The near range measurement from 0 to 5 m are realised in a measuring chamber equipped with absorber foam and nearly ideal targets like corner reflectors. The comparison of 2D-FFT and FBP algorithm shows that both deliver good and similar results for the far range measurements but the runtime of the FBP algorithm is up to 150 times longer as the 2D-FFT runtime. In the near range measurements the FBP algorithm displays a very good azimuth resolution and targets which are very close to each other can be separated easily. In contrast to that the 2D-FFT algorithm has a lower azimuth resolution in the near range, thus targets which are very close to each other, merge together and cannot be separated.
In the single-processor scheduling problem with time restrictions there is one main processor and B resources that are used to execute the jobs. A perfect schedule has no idle times or gaps on the main processor and the makespan is therefore equal to the sum of the processing times. In general, more resources result in smaller makespans, and as it is in practical applications often more economic not to mobilize resources that will be unnecessary and expensive, we investigate in this paper the problem to find the smallest number B of resources that make a perfect schedule possible. We show that the decision version of this problem is NP-complete, derive new structural properties of perfect schedules, and we describe a Mixed Integer Linear Programming (MIP) formulation to solve the problem. A large number of computational tests show that (for our randomly chosen problem instances) only B=3 or B=4 resources are sufficient for a perfect schedule.
Numerous research methods have been developed to detect anomalies in the areas of security and risk analysis. In healthcare, there are numerous use cases where anomaly detection is relevant. For example, early detection of sepsis is one such use case. Early treatment of sepsis is cost effective and reduces the number of hospital days of patients in the ICU. There is no single procedure that is sufficient for sepsis diagnosis, and combinations of approaches are needed. Detecting anomalies in patient time series data could help speed the development of some decisions. However, our algorithm must be viewed as complementary to other approaches based on laboratory values and physician judgments. The focus of this work is to develop a hybrid method for detecting anomalies that occur, for example, in multidimensional medical signals, sensor signals, or other time series in business and nature. The novelty of our approach lies in the extension and combination of existing approaches: Statistics, Self Organizing Maps and Linear Discriminant Analysis in a unique and unprecedented way with the goal of identifying different types of anomalies in real-time measurement data and defining the point where the anomaly occurs. The proposed algorithm not only has the full potential to detect anomalies, but also to find real points where an anomaly starts.