600 Technik, Medizin, angewandte Wissenschaften
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We consider a risk model in discrete time with dividends and capital injections. The goal is to maximise the value of a dividend strategy. We show that the optimal strategy is of barrier type. That is, all capital above a certain threshold is paid as dividend. A second problem adds tax to the dividends but an injection leads to an exemption from tax. We show that the value function fulfils a Bellman equation. As a special case, we consider the case of premia of size one. In this case we show that the optimal strategy is a two barrier strategy. That is, there is a barrier if a next dividend of size one can be paid without tax and a barrier if the next dividend of size one will be taxed. In both models, we illustrate the findings by de Finetti’s example.
Editorial
(2020)
In this paper we describe traffic sign recognition with neural networks in the frequency domain. Traffic signs exist in all countries to regulate the traffic of vehicles and pedestrians. Each country has its own set of traffic signs that are more or less similar. They consist of a set of abstract forms, symbols, numbers and letters, which are combined into different signs. Automatic traffic sign recognition is important for driver assistance systems and for autonomous driving. Traffic sign recognition is a subtype of image recognition. The traffic signs are usually recorded by a camera and must be recognized in real time, i.e. assigned to a class. We use neural networks for traffic sign recognition. The special feature of our method is that the traffic sign recognition does not take place in the spatial domain but in the frequency domain. This has advantages because it is possible to significantly reduce the number of neurons and thus the computing effort of the neural network compared to a conventional neural network.
This bachelor thesis addresses the issue of how school resilience can be measured and assessed quantitatively. Schools as social infrastructures have a significant value for society. Yet, on a global scale, they, and therefore the respective community as well, are continuously endangered by a variety of threats such as natural disasters or violence and mental abuse affecting students, parents and school staff. However, these threats differ greatly depending on climatic and geographical conditions as well as on the socio-cultural context of the corresponding community. To strengthen school resilience against potential threats and to ensure education continuity despite the occurrence of these disruptions, a methodology is developed to measure and assess school resilience in conjunction with its specific circumstances. Initially, qualitative and quantitative (composite) indicators are identified and categorised with the help of a Systematic Literature Review and Mayring's Qualitative Content Analysis. These are subsequently developed into a Comprehensive Index for School Resilience (CISR). Building on this, a pre-existing assessment methodology, which uses Likert-Scales arranged in questionnaires to assign quantitative values to the composite indicators, is adapted to operationalise the CISR and by an exemplary application at Europaschule Troisdorf, the methodology is adapted to the socio-cultural conditions in Germany using an expert’s operational and contextual knowledge. The results obtained show that the methodologies and techniques described in current international research can, after an appropriate adaptation, successfully be applied to schools in Germany as well. Nevertheless, by identifying research limitations and errors as well as potential improvements, it is evident that further research and development is needed to provide stakeholders with a decision-making tool to strengthen the resilience of schools in the future, such as an exhaustive supplement to the CISR or the integration of more precise quantification methodologies and techniques.
This investigation attempts to understand the eco‐hydrology of, and accordingly suggest an option to manage floodwater for agriculture in, the understudied and data‐sparse ephemeral Baraka River Basin within the hyper‐arid region of Sudan. Reference is made to the major feature of the basin, that is, the Toker Delta spate irrigation scheme. A point‐to‐pixel comparison of gridded and ground‐based data sets is performed to enhance the estimates of rainfall. Analysis of remotely sensed land use/cover data is performed. The results show a significant reduction of the grassland and barren areas explained by a significant expansion of the cropland and open shrubland (invasive mesquite trees) areas in the delta. The cotton sown area is highly dependent on the flooded area and the discharge volume in the delta. However, the area of this major crop has declined since the early 1990s in favour of cultivation of more profitable food crops. Expansion of mesquite in the delta is problematic, taking hold under increased floodwater, and can only be manged by clearance to provide crop cultivation area. There is a great potential for floodwater harvesting during the rainfall season (June to September). A total seasonal runoff volume of around 4.6 and 10.8 billion cubic metres is estimated at 90 and 50% probabilities of exceedance (reliabilities), respectively. Rather than leaving the runoff generated from rainfall events to pass to the Red Sea or be consumed by mesquite trees, a location for runoff harvesting structure in a highly suitable area is proposed. Such a structure will support any policy shifts towards planning and managing the basin water resources for use in irrigating the agricultural scheme.
Wärme‐ und Kältespeicher von Gebäuden beruhen auf verschiedenen Konzepten der Wärmeübertragung. Bei thermischen Hybridspeichern befindet sich das Phasen-wechselmaterial (PCM) makroverkapselt in PCM‐Objekten, die im Speicherbehälter positioniert sind und vom Wärmeträgerfluid umströmt werden. Die experimentellen Untersuchungen widmen sich den Belade‐ und Entladeeigenschaften des in Kugeln makroverkapselten PCM. Es wird gezeigt, dass die spezifische Wärmeübertragungs-leistung eines Hybridspeichers unmittelbar von der Größe der Kugeln als auch von der spezifischen Wärmeleitfähigkeit des PCM abhängt.
Eine gängige Form der Qualitätskontrolle von Quellcode sind Code Reviews. Der Fokus von Code Reviews liegt allerdings oft auf syntaktischer Analyse, wodurch weniger Zeit für eine semantische Überprüfung bleibt und zusätzliche Kosten verursacht werden. Code Reviews lassen sich zwar teilweise durch "Linter" automatisieren, dennoch können sie nur syntaktische Fehlermuster identifizieren, welche vorher definiert wurden. Zudem kann ein Linter nur darauf hinweisen, dass möglicherweise ein Fehler vorliegt, da die Fehler nicht durch logische Inferenz ermittelt werden. Die vorliegende Arbeit prüft, ob ein Deep Learning Modell den regelbasierten Ansatz von Lintern ablösen und die semantische Ebene erschließen kann. Dazu wurde eine Stichprobe von Java Methoden zusammengestellt und im Anschluss mit einem Supervised Learning Ansatz binär klassifiziert. Da die Analyse von Quellcode der Textanalyse stark ähnelt wird ein gängiger Ansatz für Textklassifikation verwendet. Dadurch kann gezeigt werden, dass eine Präzision von 85% bei der Erkennung von Quellcodeproblemen durch Deep Learning möglich ist.
Die Bundesregierung hat sich verpflichtet, die Treibhausgasemissionen in den nächsten Jahren stark zu senken. Potentiale hierfür werden besonders im Gebäudesektor gesehen, da dieser einen hohen Anteil des Endenergieverbrauchs verursacht. Bisher lagen für den Gebäudetypus der „Theaterspielstätte“ im Gegensatz zu anderen Gebäudetypologien weder energetische Kennwerte noch Daten zum Raumkomfort vor. Im Rahmen einer deutschlandweiten Querschnittserhebung in 13 Theaterspielstätten über den Zeitraum von drei Wochen wurden sowohl Energieverbräuche mittels zerstörungsfrei
installierter Messsensoren als auch Daten zum Raumkomfort durch den Einsatz eines Messtorsos auf Nutzerebene sowie
einer parallelen Nutzerbefragung erfasst, ausgewertet und analysiert. Anhand dieser Daten wurden charakteristische Kennwerte gebildet und ein Benchmarking erstellt. Darüber hinaus konnte der Energieverbrauch mittels TEK-Tool rechnerisch auf Nutzungszonen und Gewerke verteilt werden, sodass ein Verständnis für die Struktur des Energieverbrauchs in Theaterspielstätten entwickelt wurde, auf Basis dessen die Abschätzung energetischer Einsparpotentiale möglich ist.
Außerdem wurde durch ein einjähriges Intensivmonitoring im sanierten Scharoun Theater Wolfsburg exemplarisch das Einsparpotential durch Gebäudesanierungen und Anlagenoptimierungen von Theaterspielstätten messtechnisch erforscht. Die gemessenen Daten wurden dem Energieverbrauch vor der Sanierung sowie den Sanierungszielen gegenübergestellt und ebenso gegenüber den Kennwerten aus der Querschnittserhebung eingeordnet.
Die Erkenntnisse über die Nutzungs- und Energieverbrauchsstruktur in Theaterspielstätten können zukünftig angewendet werden, um Energieverbräuche rechnerisch besser ermitteln zu können und um Ansatzpunkte zur Reduzierung des Energieverbrauchs zu identifizieren.
As Digital Twins gain more traction and their adoption in industry increases, there is a need to integrate such technology with machine learning features to enhance functionality and enable decision making tasks. This has lead to the emergence of a concept known as Digital Triplet; an enhancement of Digital Twin technology through the addition of an ’intelligent activity layer’. This is a relatively new technology in Industrie 4.0 and research efforts are geared towards exploring its applicability, development and testing of means for implementation and quick adoption. This paper presents the design and implementation of a Digital Triplet for a three-floor elevator system. It demonstrates the integration of a machine learning (ML) object detection model and the system Digital Twin. This was done to introduce an additional security feature that enabled the system to make a decision, based on objects detected and take preliminary security measures. The virtual model was designed in Siemens NX and programmed via Total Integrated Automation (TIA) portal software. The corresponding physical model was fabricated and controlled using a Programmable Logic Controller (PLC) S7 1200. A control program was developed to mimic the general operations of a typical elevator system used in a commercial building setting. Communication, between the physical and virtual models, was enabled using the OPC-Unified Architecture (OPC-UA) protocol. Object recognition using “You only look once” (YOLOV3) based machine learning algorithm was incorporated. The Digital Triplet’s functionality was tested, ensuring the virtual system duplicated actual operations of the physical counterpart through the use of sensor data. Performance testing was done to determine the impact of the ML module on the real-time functionality aspect of the system. Experiment results showed the object recognition contributed an average of 1.083s to an overall signal travel time of 1.338 s.
Pelleted biomass has a low, uniform moisture content and can be handled and stored cheaply and safely. Pellets can be made of industrial waste, food waste, agricultural residues, energy crops, and virgin lumber. Despite their many desirable attributes, they cannot compete with fossil fuel sources because the process of densifying the biomass and the price of the raw materials make pellet production costly.
Leaves collected from street sweeping are generally discarded in landfills, but they can potentially be valorized as a biofuel if they are pelleted. However, the lignin content in leaves is not high enough to ensure the physical stability of the pellets, so they break easily during storage and transportation. In this study, the use of eucalyptus kraft lignin as an additive in tree-leaf pellet production was studied. Results showed that when 2% lignin is added the abrasion resistance can be increased to an acceptable value. Pellets with added lignin fulfilled all requirements of European standards for certification except for ash content. However, as the raw material has no cost, this method can add value or contribute to financing continued sweeping and is an example of a circular economy scenario.