Hochschule Konstanz University of Applied Sciences
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Ten key principles: How to communicate climate change for effective public engagement
Get PDFThis report summarises up-to-date social science evidence on climate communication for effective public engagement. It presents ten key principles that may inform communication activities. At the heart of them is the following insight: People do not form their attitudes or take action as a result primarily of weighing up expert information and making rational cost-benefit calculations. Instead, climate communication has to connect with people at the level of values and emotions.
Two aspects seem to be of special importance: First, climate communication needs to focus more on effectively speaking to people who have up to now not been properly addressed by climate communications, but who are vitally important to build broad public engagement. Second, climate communication has to support a shift from concern to agency, where high levels of climate risk perception turn into pro-climate individual and collective action
Automatisiertes Erkennen von Polygonzügen aus Grundrissbildern
Get PDFDer Gegenstand dieser Bachelorarbeit ist die automatisierte Extraktion von Polygonzügen anhand eines Grundrissbildes. Diese Polygonzüge sollen die Räumlichkeiten wiedergeben. In dieser Bachelorarbeit wurde daher ein Algorithmus für die Grundrissbildverarbeitung mittels Python entwickelt und implementiert. Zuerst wird ein Grundrissbild bereinigt, d. h. es werden unerwünschte Bildstrukturen verwaschen. Mithilfe des Canny-Kantendetektors werden anschließend die Kanten detektiert. Danach werden die Ecken im Grundrissbild via Harris-Eckendetektor lokalisiert. Um die Ecken sinnvoll zu verbinden, wird eine abgewandelte Form des Dijkstra Algorithmus herangezogen. Die daraus gewonnen Daten dienen zur Erstellung der Polygonzüge, welche für die Simulation von pFlow benötigt werden. Der entwickelte Algorithmus eignet sich insbesondere für klare und simple Grundrissbilder.The subject of this bachelor thesis is the automated extraction of polygons from a floor plan image. These polygons are supposed to represent the rooms. Therefore, an algorithm for image processing of floor plans was developed and implemented by using Python in this bachelor thesis. First, a floor plan image is cleaned up, i.e. unwanted image structures are washed out. Then the edges are detected by using the Canny edge detector. Afterwards, corners of the floor plan are localized with the help of the Harris corner detector. To connect the corners in a meaningful way, a modified form of Dijkstra's algorithm is used. The resulting data is used to create the polygons, which are needed for the simulation of pFlow. The developed algorithm is especially suitable for clear and simple floor plan images
Extended Target Tracking With a Lidar Sensor Using Random Matrices and a Virtual Measurement Model
No full textRandom matrices are widely used to estimate the extent of an elliptically contoured object. Usually, it is assumed that the measurements follow a normal distribution, with its standard deviation being proportional to the object’s extent. However, the random matrix approach can filter the center of gravity and the covariance matrix of measurements independently of the measurement model. This work considers the whole chain from data acquisition to the linear Kalman Filter with extension estimation as a reference plant. The input is the (unknown) ground truth (position and extent). The output is the filtered center of gravity and the filtered covariance matrix of the measurement distribution. A virtual measurement model emulates the behavior of the reference plant. The input of the virtual measurement model is adapted using the proposed algorithm until the output parameters of the virtual measurement model match the result of the reference plant. After the adaptation, the input to the virtual measurement model is considered an estimation for position and extent. The main contribution of this paper is the reference model concept and an adaptation algorithm to optimize the input of the virtual measurement model
A real time capable PDE model for an industrial heating process
No full textThis paper presents a modeling approach of an industrial heating process where a stripe-shaped workpiece is heated up to a specific temperature by applying hot air through a nozzle. The workpiece is moving through the heating zone and is considered to be of infinite length. The speed of the substrate is varying over time. The derived model is supposed to be computationally cheap to enable its use in a model-based control setting. We start by formulating the governing PDE and the corresponding boundary conditions. The PDE is then discretized on a spatial grid using finite differences and two different integration schemes, explicit and implicit, are derived. The two models are evaluated in terms of computational effort and accuracy. It turns out that the implicit approach is favorable for the regarded process. We optimize the grid of the model to achieve a low number of grid nodes while maintaining a sufficient amount of accuracy. Finally, the thermodynamical parameters are optimized in order to fit the model's output to real-world data that was obtained by experiments
Apnea-hypopnea index using deep learning models with whole and window-based time series
No full textoday many scientific works are using deep learning algorithms and time series, which can detect physiological events of interest. In sleep medicine, this is particularly relevant in detecting sleep apnea, specifically in detecting obstructive sleep apnea events. Deep learning algorithms with different architectures are used to achieve decent results in accuracy, sensitivity, etc. Although there are models that can reliably determine apnea and hypopnea events, another essential aspect to consider is the explainability of these models, i.e., why a model makes a particular decision. Another critical factor is how these deep learning models determine how severe obstructive sleep apnea is in patients based on the apnea-hypopnea index (AHI). Deep learning models trained by two approaches for AHI determination are exposed in this work. Approaches vary depending on the data format the models are fed: full-time series and window-based time series
Neural network aided reference voltage adaptation for NAND flash memory
No full textLarge persistent memory is crucial for many applications in embedded systems and automotive computing like AI databases, ADAS, and cutting-edge infotainment systems. Such applications require reliable NAND flash memories made for harsh automotive conditions. However, due to high memory densities and production tolerances, the error probability of NAND flash memories has risen. As the number of program/erase cycles and the data retention times increase, non-volatile NAND flash memories' performance and dependability suffer. The read reference voltages of the flash cells vary due to these aging processes. In this work, we consider the issue of reference voltage adaption. The considered estimation procedure uses shallow neural networks to estimate the read reference voltages for different life-cycle conditions with the help of histogram measurements. We demonstrate that the training data for the neural networks can be enhanced by using shifted histograms, i.e., a training of the neural networks is possible based on a few measurements of some extreme points used as training data. The trained neural networks generalize well for other life-cycle conditions
A tourism research agenda for Uzbekistan
No full textUzbekistan is an emerging tourism destination that has experienced a strong increase in tourists since 2017. However, little research on tourism development in Uzbekistan exists to date. This study therefore analyzes possible research topics and proposes a tourism research agenda for Uzbekistan. A mix of methods was used consisting of participant observation, semi-structured qualitative expert interviews and qualitative content anal- ysis. The results revealed a variety of research deficits in different areas, which could be synthesized into a total of ten research fields, which were clustered into three overarching areas, namely market research, management, and culture & environment. The subordi- nate research fields identified are Demand, Statistics, Potentials, Governance, Products, Infrastructure & Development, Marketing, Heritage & Nation-building, Sustainability as well as Peace & Conflict Prevention. A strategic research plan based on this tourism research agenda could help to foster a purposeful scientific debate. Tourism research in these fields has both the potential to investigate and compare theoretical issues in an unique context and to produce applied research results that can make a relevant contri- bution to tourism development in Uzbekistan
Diseño y desarrollo de soluciones digitales exhaustivas aplicadas al ámbito médico: análisis del sueño en humanos
No full textThe influence of sleep on human life, including physiological, psychological, and mental aspects, is remarkable. Therefore, it is essential to apply appropriate therapy in the case of sleep disorders. For this, however, the irregularities must first be recognised, preferably conveniently for the person concerned. This dissertation, structured as a composition of research articles, presents the development of mathematically based algorithmic principles for a sleep analysis system. The particular focus is on the classification of sleep stages with a minimal set of physiological parameters. In addition, the aspects of using the sleep analysis system as part of the more complex healthcare systems are explored. Design of hardware for non-obtrusive measurement of relevant physiological parameters and the use of such systems to detect other sleep disorders, such as sleep apnoea, are also referred to. Multinomial logistic regression was selected as the basis for development resulting from the investigations carried out. By following a methodical procedure, the number of physiological parameters necessary for the classification of sleep stages was successively reduced to two: Respiratory and Movement signals. These signals might be measured in a contactless way. A prototype implementation of the developed algorithms was performed to validate the proposed method, and the evaluation of 19324 sleep epochs was carried out. The results, with the achieved accuracy of 73% in the classification of Wake/NREM/REM stages and Cohen's kappa of 0.44, outperform the state of the art and demonstrate the appropriateness of the selected approach. In the future, this method could enable convenient, cost-effective, and accurate sleep analysis, leading to the detection of sleep disorders at an early stage so that therapy can be initiated as soon as possible, thus improving the general population's health status and quality of life.La influencia del sueño en la vida humana, incluidos los aspectos fisiológicos, psicológicos y mentales, es notable. Por tanto, es fundamental aplicar la terapia adecuada para los trastornos del sueño. Para conseguirlo, es necesario en primer término reconocer los trastornos que presenta la persona afectada. En esta tesis, estructurada como un compendio de artículos de investigación, se presenta el desarrollo de los principios algorítmicos con base matemática para un sistema de análisis del sueño. Se hace especial hincapié en la clasificación de las etapas del sueño con un conjunto mínimo de parámetros fisiológicos. Además, se exploran los aspectos de la utilización del sistema de análisis del sueño como parte de sistemas sanitarios más complejos. También se hace referencia al diseño de hardware para la medición no intrusiva de los parámetros fisiológicos relevantes en el análisis del sueño y el uso de estos sistemas para detectar otros trastornos, como el de la apnea del sueño. Se ha seleccionado la regresión logística multinomial como base del desarrollo en las investigaciones realizadas. Siguiendo un procedimiento metódico, el número de parámetros fisiológicos necesarios para la clasificación de las etapas del sueño se ha ido reduciendo hasta conseguirlo con tan sólo dos: señales respiratorias y de movimiento. Estas señales pueden medirse de manera no invasiva, esto es, sin contacto. La validar del método propuesto en la tesis se ha conseguido implementando un prototipo con los algoritmos desarrollados y se han probado evaluando 19324 épocas de sueño. Los resultados obtenidos han conseguido una precisión del 73% en la clasificación de las etapas de vigilia/NREM/REM y un kappa de Cohen de 0,44, mejorando a los existentes en el estado del arte y demostrando la idoneidad del enfoque realizado. En el futuro, este método podría permitir un análisis del sueño cómodo, rentable y preciso, lo que permitiría detectar los trastornos del sueño en una fase temprana para poder iniciar la terapia lo antes posible, mejorando así el estado de salud y la calidad de vida de la población en general