C Mathematical and Quantitative Methods
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Mangrove forests have been studied broadly in the recent three decades for their outstanding ability to sequester carbon in the beneath soil and other beneficial ecosystem services. Endeavors to conserve and regenerate mangrove cover are still increasing worldwide as a mechanism to include them in NDCs and carbon markets. Therefore, decision-makers in the private and public sectors require identify possible areas for conservation and restoration prior to blue carbon project investment. Thus, an integral assessment of potential mangrove carbon reservoirs in a landscape scale, considering environmental and socioeconomic factors was performed. This study was aimed to determine areas with the highest blue carbon sequestration potential in the Gulf of Guayaquil through the construction of a Blue Carbon Potential Index (BCPI) based on Spatial Multicriteria Analysis (SMCA). A narrative integrative literature review was employed to select indicators of mangrove carbon sequestration gains and losses. These indicators were pondered following the Analytical Hierarchy Process (AHP) with the judgments of two experts and reclassified in four potential categories based on their thresholds. Since no consensus was achieved in the indicator importance hierarchization, a comparative of equal weighting method and AHP weighting was implemented. The linear combination rule was used to integrate these factors into a unique-scaled index supported by a geographic Information System (GIS). The results showed that 15.82% and 16.21% of the study area belonged to high and moderate potential of blue carbon sequestration respectively. Moreover, no significant differences were found between the two weighting methods applied. The BCPI provides a comprehensive understanding of spatial distribution of blue carbon potential reservoirs and grants a quantification of this potential to prioritize conservation and restoration areas.
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.
A test tool for Langton's ant-based algorithms is created. Among other things, it can create test files for the NIST-Statistical-Test-Suite. The test tool is used to investigate the invertibility, ring formation and randomness of 7 created models which are extensions of Langton’s ant. The models are examined to possibly use them as pseudo-random generator (PRG) or block cipher. All models use memories which are based on tori. This property is central, because this is how rings are formed in the first place and in addition the behavior of all models at the physical boundaries of the memory is clearly defined in this way. The different models have special properties which are also investigated. These include variable color sets, discrete convolution, multidimensionality, and the use of multiple ants, which are arranged fractal hierarchically and influence each other. The extensions convolution, multidimensional scalable and multidimensional scalable fractal ant colony are presented here for the first time. It is shown that well-chosen color sets and high-dimensional tori are particularly well suited as a basis for Langton's ant based PRGs. In addition, it is shown that a block cipher can be generated on this basis.
REST became the go to approach when it comes to large scale distributed systems on, or outside the World Wide Web. This paper aims to give a brief overview of what REST is and what its main draws and benefits are. Secondly, I will showcase the implementation of REST using HTTP and why this approach became as popular as it is today. Based on my research I concluded that REST’s advantages in scalability, coupling, performance and its seamless integration with HTTP enabled it to rightfully overtake classic RPC based approaches.
This thesis presents the perspective and basis for modeling of retail electricity price components in Germany. Detailed Python models are developed to provide predictions for yearly development of average network charges, EEG, StromNEV-19 and KWK surcharges for the period 2015-2035. For network charges and EEG surcharge, scenario-B (2035) from NEP2015 has been chosen as the model scenario. For KWK surcharge, the 2025 KWK share target, set by KWKG-2016, has been chosen as the model scenario. Individual component model results are validated against available academic literature and institutional reports. Model results for EEG surcharge, indicate an increasing yearly EEG costs till 2024, after which the expiring EEG plants of past will unburden the related high costs and EEG surcharge will drop but still be around 99% of 2015 level in 2035. Model results for network charges indicate a consistently increasing yearly trend owing to high grid investments needed for reaching the target RE share of 57%. KWK model results also indicate a growing KWK surcharge until 2020 which then would remain stagnant at that level onwards. All model results are collected under three consumption categories, namely, households, privileged and nonprivileged industries. The final results indicate that the average German household will face an overall increase of around 3.37 Cents/kWh in retail electricity prices (excluding VAT) till 2028, after which the retail prices will drop a little due to dropping EEG surcharge. The similar but slightly reduced trend can be seen for nonprivileged industrial consumption. The increment effect, however, is only minute for privileged industrial consumption due to high exemptions in EEG & KWK surcharges and reduced individual network charges.