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Dynamic Programming
(2024)
Queueing Theory
(2024)
The Decision Tree Procedure
(2024)
Heuristic Methods
(2024)
Network Analysis Method
(2024)
Farming communities confronted with climate change adopt formal and informal adaptation strategies to mitigate the effects of climate change. While the environmental and social effects of climate change are well documented, there is still a dearth of literature on girl-child marriage (formal marriage or informal union between a child under the age of 18 and an adult or another child) as a response to the effects of climate change. In this research, we ask if girl-child marriage is promoted as a social protection mechanism first, rather than as simply a response to climate-induced poverty. We use qualitative semi-structured interviews and focus group discussions to explore this question in a rural farming community in Northern Ghana. Our findings reveal that climate change shocks result in poverty and compel farmers to marry off their young daughters. The unmarried girl-child is perceived as an ‘extra mouth to feed’, a liability whose marriage becomes a strategy for protecting the family, the family’s reputation, and the girl child. The emphasis in girl-child marriage is not on the girl-child as an individual but on the family as a group. Hence, what is good for the family is assumed to be in the best interest of the girl-child. We place our analysis at the intersection of climate change, social protection, and the incidence of girl-child marriages. We argue that understanding this link is crucial and can contribute significantly to our knowledge of girl-child marriage as well as our ability to address this in Sub-Saharan Africa.
Integrating physical simulation data into data ecosystems challenges the compatibility and interoperability of data management tools. Semantic web technologies and relational databases mostly use other data types, such as measurement or manufacturing design data. Standardizing simulation data storage and harmonizing the data structures with other domains is still a challenge, as current standards such as the ISO standard STEP (ISO 10303 ”Standard for the Exchange of Product model data”) fail to bridge the gap between design and simulation data. This challenge requires new methods, such as ontologies, to rethink simulation results integration. This research describes a new software architecture and application methodology based on the industrial standard ”Virtual Material Modelling in Manufacturing” (VMAP). The architecture integrates large quantities of structured simulation data and their analyses into a semantic data structure. It is capable of providing data permeability from the global digital twin level to the detailed numerical values of data entries and even new key indicators in a three-step approach: It represents a file as an instance in a knowledge graph, queries the file’s metadata, and finds a semantically represented process that enables new metadata to be created and instantiated.
The Information and Communication Technology (ICT) sector is a significant global industry, and addressing climate change is of critical importance. This paper aims to assess the resources utilized by the ICT sector, the associated negative environmental impacts, and potential mitigation measures. In order to understand these aspects, this study attempts to categorize the resources used by ICT, analyze the amount consumed and the resulting negative impacts, and determine what measures exist to mitigate them. An economic and empirical evaluation shows a negative trend in ICT’s resource consumption, mainly due to increased energy consumption and rising carbon emissions from devices such as smartphones and data centers. The investigated countermeasures focus on Green IT strategies that encompass energy efficiency, carbon awareness, and hardware efficiency principles as outlined by the Green Software Foundation. Special attention is given to reducing the environmental footprint of data center operations and smartphones. This paper concludes that Green IT strategies, although promising in theory, are often not implemented at an industry level.
Accurate global horizontal irradiance (GHI) forecasting is critical for integrating solar energy into the power grid and operating solar power plants. The Weather Research and Forecasting model with its solar radiation extension (WRF-Solar) has been used to forecast solar irradiance in different regions around the world. However, the application of the WRF-Solar model to the prediction of GHI in West Africa, particularly Ghana, has not yet been investigated. The aim of this study is to evaluate the performance of the WRF-Solar model for predicting GHI in Ghana, focusing on three automatic weather stations (Akwatia, Kumasi and Kologo) for the year 2021. We used two one-way nested domains (D1 = 15 km and D2 = 3 km) to investigate the ability of the fully coupled WRF-Solar model to forecast GHI up to 72-hour ahead under different atmospheric conditions. The initial and lateral boundary conditions were taken from the ECMWF high-resolution operational forecasts. Our findings reveal that the WRF-Solar model performs better under clear skies than cloudy skies. Under clear skies, Kologo performed best in predicting 72-hour GHI, with a first day nRMSE of 9.62 %. However, forecasting GHI under cloudy skies at all three sites had significant uncertainties. Additionally, WRF-Solar model is able to reproduce the observed GHI diurnal cycle under high AOD conditions in most of the selected days. This study enhances the understanding of the WRF-Solar model’s capabilities and limitations for GHI forecasting in West Africa, particularly in Ghana. The findings provide valuable information for stakeholders involved in solar energy generation and grid integration towards optimized management in the region.
The Peren-Clement Index
(2024)
Sequencing Problems
(2024)
Linear Optimization
(2024)