Hochschule Bonn-Rhein-Sieg
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Advanced Rapid Directional Over-Current Protection for DC Microgrids Using K-Means Clustering
No full textWhen the "Matchmaker" Does Not Have Your Interest at Heart: Perceived Algorithmic Harms, Folk Theories, and Users' Counter-Strategies on Tinder
No full textRecommendations for effective insect conservation in nature protected areas based on a transdisciplinary project in Germany
No full textThe decline of insect abundance and richness has been documented for decades and has received increased attention in recent years. In 2017, a study by Hallmann and colleagues on insect biomasses in German nature protected areas received a great deal of attention and provided the impetus for the creation of the project Diversity of Insects in Nature protected Areas (DINA). The aim of DINA was to investigate possible causes for the decline of insects in nature protected areas throughout Germany and to develop strategies for managing the problem. A major issue for the protection of insects is the lack of insect-specific regulations for nature protected areas and the lack of a risk assessment and verification of the measures applied. Most nature protected areas border on or enclose agricultural land and are structured in a mosaic, resulting in an abundance of small and narrow areas. This leads to fragmentation or even loss of endangered habitats and thus threaten biodiversity. In addition, the impact of agricultural practices, especially pesticides and fertilisers, leads to the degradation of biodiversity at the boundaries of nature protected areas, reducing their effective size. All affected stakeholders need to be involved in solving these threats by working on joint solutions. Furthermore, agriculture in and around nature protected areas must act to promote biodiversity and utilise and develop methods that reverse the current trend. This also requires subsidies from the state to ensure economic sustainability and promote biodiversity-promoting practices
Exploring the Boundaries of Digitalization of Cultural Heritage: Opportunities, Challenges and Future Directions
No full textThis contribution explores the opportunities and challenges of digitalizing cultural heritage, using the Digitalization of Cultural Heritage project as a case study. The project, a collaboration among universities from multiple countries, focuses on creating 3D models of historical artifacts, exemplified by the 3D modelling of Roman-period fragments using photogrammetry. The paper discusses the broader implications of digitalization with a particular focus on the use of AI technologies, including its potential to enhance education, accessibility, artifact preservation, and cultural tourism. It also addresses the technical and ethical challenges involved, emphasizing the need for ongoing innovation and interdisciplinary collaboration to maximize the benefits of digital cultural preservation.This contribution explores the opportunities and challenges of digitalizing cultural heritage, using the Digitalization of Cultural Heritage project as a case study. The project, a collaboration among universities from multiple countries, focuses on creating 3D models of historical artifacts, exemplified by the 3D modelling of Roman-period fragments using photogrammetry. The paper discusses the broader implications of digitalization with a particular focus on the use of AI technologies, including its potential to enhance education, accessibility, artifact preservation, and cultural tourism. It also addresses the technical and ethical challenges involved, emphasizing the need for ongoing innovation and interdisciplinary collaboration to maximize the benefits of digital cultural preservation
A new bottom-up method for classifying a building portfolio by building type, self-sufficiency rate, and access to local grid infrastructure for storage demand analysis
No full textA building’s energy storage demand depends on a variety of factors related to the specific local conditions such as building type, self-sufficiency-rate, and grid connection. Here, a newly developed bottom-up procedure is presented for classifying buildings in an urban building portfolio according to specific criteria. The algorithm uses publicly available building data such as building use, ground floor area, roof ridge height, solar roof potential, and population statistics. In addition, it considers the local gas grid (GG) as well as the district heating (DH) network. The building classification is developed for identifying typical building situations that can be used to estimate the demand for residential energy storage capacity. The developed algorithm is used to identify potential implementation of private photovoltaic(PV)-metal-hydride-storage (MHS) systems, for three scenarios, into the urban infrastructure for the city of Cologne. As result the statistical confidence interval of all analyzed buildings regarding their classification as well as corresponding maps is shown. Since similar data sets as used are available for many German or European metropolitan areas, the method developed with the assumptions presented in this work, can be used for classification of other urban and semi-urban areas including the assessment of their grid infrastructure
