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Was ist ein KI-System im Sinne der KI-VO? — Erste Ansätze zur praktischen Abgrenzung „normaler“ Systeme der Informationsverarbeitung
No full textAssessing the Resilience of Soils to Acidification on Different Time Scales
Get PDFTo estimate the sensitivity of soils to naturally and anthropogenic induced acidification we measured Acid Neutralizing Capacities (ANC) of typical soils in West Germany. Measured values of ANC are strongly dependent on the procedure employed. We conducted three kinds of experiments to distinguish between 1. Short-Term Acid Neutralizing Capacity (STANC) due to exchange processes and dissolution of easily weatherable non-silicate minerals, on the scale of days to years, 2. Medium-Term Acid Neutralizing Capacity (MTANC) due to dissolution of easily weatherable silicate minerals, on the scale of decades and 3. Long-Term Acid Neutralizing Capacity (LTANC) considering the buffer capacity of stable minerals, on the scale of centuries. The experiments have been applied on soil profiles at forest and agricultural sites with soil parent material ranging from Holocene sediments, Pleistocene loess, and Devonian sedimentary rock (greywacke/shale). Calculated acid neutralizing capacities ranged from 12.9meq kg-1 to 747meq kg-1 (STANC) depending on target pH, 580meq kg-1 to 3680meq kg-1 (MTANC) and 2841meq kg-1 to 12233meq kg-1 (LTANC). Only 11% to 19% of the MT- and LTANC can be explained by a release of basic cations (Ca, Mg, K, Na) and Mn. Thus, the remaining buffer capacity is associated with Al and Fe. These elements do not buffer protons until pH <4.8 (Al) and <3 (Fe), respectively. Because of the beginning Al-toxicity below pH 4.8 only the basic cation fraction of MTANC and LTANC should be taken into consideration when assessing soils in terms of acidification endangerment
Thermo-chemical conversion of cucumber peel waste for biobased energy and chemical production
No full text"You Can either Blame Technology or Blame a Person..." --- A Conceptual Model of Users' AI-Risk Perception as a Tool for HCI
No full textAI-powered systems pose unknown challenges for designers, policymakers, and users, making it more difficult to assess potential harms and outcomes. Although understanding risks is a requirement for building trust in technology, users are often excluded from risk assessments and explanations in policy and design. To address this issue, we conducted three workshops with 18 participants and discussed the EU AI Act, which is the European proposal for a legal framework for AI regulation. Based on results of these workshops, we propose a user-centered conceptual model with five risk dimensions (Design and Development, Operational, Distributive, Individual, and Societal) that includes 17 key risks. We further identify six criteria for categorizing use cases. Our conceptual model (1) contributes to responsible design discourses by connecting the risk assessment theories with user-centered approaches, and (2) supports designers and policymakers in more strongly considering a user perspective that complements their own expert views
Computer-Assisted Short Answer Grading Using Large Language Models and Rubrics
No full textGrading student answers and providing feedback are essential yet time-consuming tasks for educators. Recent advancements in Large Language Models (LLMs), including ChatGPT, Llama, and Mistral, have paved the way for automated support in this domain. This paper investigates the efficacy of instruction-following LLMs in adhering to predefined rubrics for evaluating student answers and delivering meaningful feedback. Leveraging the Mohler dataset and a custom German dataset, we evaluate various models, from commercial ones like ChatGPT to smaller open-source options like Llama, Mistral, and Command R. Additionally, we explore the impact of temperature parameters and techniques such as few-shot prompting. Surprisingly, while few-shot prompting enhances grading accuracy closer to ground truth, it introduces model inconsistency. Furthermore, some models exhibit non-deterministic behavior even at near-zero temperature settings. Our findings highlight the importance of rubrics in enhancing the interpretability of model outputs and fostering consistency in grading practices
Erste Änderungsordnung der Bachelor-Prüfungsordnung Technikjournalismus vom 22. Februar 2018 am Standort Sankt Augustin der Hochschule Bonn-Rhein-Sieg in der Fassung vom 25. April 2024
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Optimal placement and upgrade of solar PV integration in a grid-connected solar photovoltaic system
No full textThe shift towards renewable energy sources has heightened the interest in solar photovoltaic (SPV) systems, particularly in grid-connected configurations, to enhance energy security and reduce carbon emissions. Grid-tied SPVs face power quality challenges when specific grid codes are compromised. This study investigates and upgrades an integrated 90 kWp solar plant within a distribution network, leveraging data from Ghana's Energy Self-Sufficiency for Health Facilities (EnerSHelF) project. The research explores four scenarios for SPV placement optimization using dynamic programming and the Conditional New Adaptive Foraging Tree Squirrel Search Algorithm (CNAFTSSA). A Python-based simulation identifies three scenarios, high load nodes, voltage drop nodes, and system loss nodes, as the points for placing PV for better performance. The analysis revealed 85 %, 82.88 %, and 100 % optimal SPV penetration levels for placing the SPV at high load, voltage drop, and loss nodes. System active power losses were reduced by 72.97 %, 71.52 %, and 70.15 %, and reactive power losses by 73.12 %, 71.86 %, and 68.11 %, respectively, by placing the SPV at the above three categories of nodes. The fourth scenario applies to CNAFTSSA, achieving 100 % SPV penetration and reducing active and reactive power losses by 72.33 % and 72.55 %, respectively. This approach optimizes the voltage regulation (VR) from 24.92 % to 4.16 %, outperforming the VR of PV placement at high load nodes, voltage drop nodes, and loss nodes, where the voltage regulations are 5.25 %, 9.36 %, and 9.64 %, respectively. The novel CNAFTSSA for optimal SPV placement demonstrates its effectiveness in achieving higher penetration levels and improving system losses and VR. The findings highlight the effectiveness of strategic SPV placement and offer a comprehensive methodology that can be adapted for similar power distribution systems