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Die Hitzewellen der Sommer 2003 und 2015 zeigten wie kritisch langanhaltende Trockenheit nicht nur für die Natur, sondern auch für wassernutzende Unternehmen werden kann. Infolge des Klimawandels wird es entlang der Gewässer Baden-Württembergs immer wieder zu verschärften Niedrigwassersituationen kommen, was unter Umständen zu Wassernutzungskonflikten mit anderen Nutzern führt. Innerhalb dieses KLIMOPASS Projektes liegt der Fokus auf der Identifikation von vorhandenen und im Zuge des Klimawandels potenziell auftretenden lnteressens- und Nutzungskonflikten um die Ressource Wasser. Der Forschungsschwerpunkt bezieht sich hierbei auf zwei beispielhafte Fluss-Einzugsgebiete in Baden-Württemberg (die Murg und der Kocher) sowie aller beteiligten Akteure bzw. Wasserge- und -verbraucher (Energienutzung, Landwirtschaft, kommunale Entwässerung, Tourismus, Ökologie, etc.).
Anhand des Kochers und der Murg wurden mit Hilfe von Umfragen, Experteninterviews und Workshops Nutzungskonflikte identifiziert sowie Handlungsoptionen für eine Niedrigwasservorsorge und ein Niedrigwassermanagement erstellt. Dabei galt es ökonomische, gesellschaftliche und ökologische Belange möglichst adäquat zu berücksichtigen und sämtliche relevanten Akteure (Stakeholder) in einen partizipativen Prozess zu integrieren. Den Erhebungen zufolge treten Wassernutzungskonflikte nicht allgemein sektorenübergreifend auf, sondern sektorenspezifisch. Hierbei stehen die in Konflikte verwickelten Sektoren charakteristischerweise mit mehreren Stakeholder-Gruppen im Widerstreit, andere Akteursgruppen haben wiederum keinerlei Erfahrung mit Konflikten. Weiterhin ist auffällig, dass Niedrigwassersituationen an beiden untersuchten Flüssen lediglich einen Teil der Nutzungskonflikte ausmachen und verstärkt mit anthropogenen Einflüssen in Verbindung gebracht werden.
This diploma thesis is devoted to the design and analysis of a radar signal enabling an object classification capability in surveillance radar systems based on high-resolution radar range profiles. It picks up the research results from Kastinger (2006), who investigated classification algorithms for high-resolution radar range profiles, and Meier (2007), who programmed a MATLAB toolbox for the evaluation of radar signals. A classical, brief, introduction to radar fundamentals is given (Chapter 1) as well as the motivation for this thesis and certain basic parameters used. After high-resolution radar range profiles are discussed with special focus on surveillance radar systems (Chapter 2), the results of Kastinger (2006) are picked up (Chapter 3) as far as necessary for the following chapters of this thesis. Following the chapters on radar basics, high-resolution radar range profiles and classification, basic and advanced radar signals are discussed and analysed, especially their range resolution and sidelobe levels (Chapter 4). This includes linear frequency-modulated pulses and nonlinear frequency-modulated pulses as well as phase-coded pulses, coherent trains of identical pulses, and stepped-frequency waveforms. Their analysis is based on Meier's MATLAB toolbox. In Chapter 5 we will bring up additional points that have to be considered in radar system design for implementing a classification capability, before this thesis ends with an overall conclusion (Chapter 6).
Analysing observability is an important step in the
process of designing state feedback controllers. While for linear
systems observability has been widely studied and easy-to-check
necessary and sufficient conditions are available, for nonlinear
systems, such a general recipe does not exist and different classes
of systems require different techniques. In this paper, we analyse
observability for an industrial heating process where a stripe-
shaped plastic workpiece is moving through a heating zone where
it is heated up to a specific temperature by applying hot air to its
surface through a nozzle. A modeling approach for this process
is briefly presented, yielding a nonlinear Ordinary Differential
Equation model. Sensitivity-based observability analysis is used
to identify unobservable states and make suggestions for addi-
tional sensor locations. In practice, however, it is not possible
to place additional sensors, so the available measurements are
used to implement a simple open-loop state estimator with
offset compensation and numerical and experimental results are
presented.
A constructive nonlinear observer design for self-sensing of digital (ON/OFF) single coil electromagnetic actuators is studied. Self-sensing in this context means that solely the available energizing signals, i.e., coil current and driving voltage are used to estimate the position and velocity trajectories of the moving plunger. A nonlinear sliding mode observer is considered, where the stability of the reduced error dynamics is analyzed by the equivalent control method. No simplifications are made regarding magnetic saturation and eddy currents in the underlying dynamical model. The observer gains are constructed by taking into account some generic properties of the systems nonlinearities. Two possible choices of the observer gains are discussed. Furthermore, an observer-based tracking control scheme to achieve sensorless soft landing is considered and its closed-loop stability is studied. Experimental results for observer-based soft landing of a fast-switching solenoid valve under dry conditions are presented to demonstrate the usefulness of the approach.
Background: Polysomnography (PSG) is the gold standard for detecting obstructive sleep apnea (OSA). However, this technique has many disadvantages when using it outside the hospital or for daily use. Portable monitors (PMs) aim to streamline the OSA detection process through deep learning (DL).
Materials and methods: We studied how to detect OSA events and calculate the apnea-hypopnea index (AHI) by using deep learning models that aim to be implemented on PMs. Several deep learning models are presented after being trained on polysomnography data from the National Sleep Research Resource (NSRR) repository. The best hyperparameters for the DL architecture are presented. In addition, emphasis is focused on model explainability techniques, concretely on Gradient-weighted Class Activation Mapping (Grad-CAM).
Results: The results for the best DL model are presented and analyzed. The interpretability of the DL model is also analyzed by studying the regions of the signals that are most relevant for the model to make the decision. The model that yields the best result is a one-dimensional convolutional neural network (1D-CNN) with 84.3% accuracy.
Conclusion: The use of PMs using machine learning techniques for detecting OSA events still has a long way to go. However, our method for developing explainable DL models demonstrates that PMs appear to be a promising alternative to PSG in the future for the detection of obstructive apnea events and the automatic calculation of AHI.
As interest in the investigation of possible sources and environmental sinks of technology-critical elements (TCEs) continues to grow, the demand for reliable background level information of these elements in environmental matrices increases. In this study, a time series of ten years of sediment samples from two different regions of the German North Sea were analyzed for their mass fractions of Ga, Ge, Nb, In, REEs, and Ta (grain size fraction < 20 µm). Possible regional differences were investigated in order to determine preliminary reference values for these regions. Throughout the investigated time period, only minor variations in the mass fractions were observed and both regions did not show significant differences. Calculated local enrichment factors ranging from 0.6 to 2.3 for all TCEs indicate no or little pollution in the investigated areas. Consequently, reference values were calculated using two different approaches (Median + 2 median absolute deviation (M2MAD) and Tukey inner fence (TIF)). Both approaches resulted in consistent threshold values for the respective regions ranging from 158 µg kg−1 for In to 114 mg kg−1 for Ce. As none of the threshold values exceed the observed natural variation of TCEs in marine and freshwater sediments, they may be considered baseline values of the German Bight for future studies.