TY - JOUR A1 - Frank, Florian A1 - Böttger, Simon A1 - Mexis, Nico A1 - Anagnostopoulos, Nikolaos Athanasios A1 - Mohamed, Ali A1 - Hartmann, Martin A1 - Kuhn, Harald A1 - Helke, Christian A1 - Arul, Tolga A1 - Katzenbeisser, Stefan A1 - Hermann, Sascha T1 - CNT-PUFs: highly robust and heat-tolerant carbon-nanotube-based physical unclonable functions N2 - In this work, we explored a highly robust and unique Physical Unclonable Function (PUF) based on the stochastic assembly of single-walled Carbon NanoTubes (CNTs) integrated within a wafer-level technology. Our work demonstrated that the proposed CNT-based PUFs are exceptionally robust with an average fractional intra-device Hamming distance well below 0.01 both at room temperature and under varying temperatures in the range from 23 °C to 120 °C. We attributed the excellent heat tolerance to comparatively low activation energies of less than 40 meV extracted from an Arrhenius plot. As the number of unstable bits in the examined implementation is extremely low, our devices allow for a lightweight and simple error correction, just by selecting stable cells, thereby diminishing the need for complex error correction. Through a significant number of tests, we demonstrated the capability of novel nanomaterial devices to serve as highly efficient hardware security primitives. KW - Carbon NanoTube (CNT) KW - Physical Unclonable Function (PUF) KW - Nanomaterials (NMs) KW - hardware security KW - security KW - privacy KW - Internet of Things (IoT) Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-14011 VL - 2023 IS - 13(22) PB - MDPI CY - Basel ER - TY - JOUR A1 - Caspari-Sadeghi, Sima T1 - Artificial Intelligence in Technology-Enhanced Assessment: A Survey of Machine Learning JF - Journal of Educational Technology Systems N2 - Intelligent assessment, the core of any AI-based educational technology, is defined as embedded, stealth and ubiquitous assessment which uses intelligent techniques to diagnose the current cognitive level, monitor dynamic progress, predict success and update students’ profiling continuously. It also uses various technologies, such as learning analytics, educational data mining, intelligent sensors, wearables and machine learning. This can be the key to Precision Education (PE): adaptive, tailored, individualized instruction and learning. This paper explores (a) the applications of Machine Learning (ML) in intelligent assessment, and (b) the use of deep learning models in ‘knowledge tracing and student modeling’. The paper concludes by discussing barriers involved in using state-of-the-art ML methods and some suggestions to unleash the power of data and ML to improve educational decision-making. KW - artificial intelligence KW - knowledge tracing KW - machine learning KW - technology-enhanced assessment (TEA) Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-11818 SN - 0047-2395 SN - 1541-3810 VL - 51 IS - 3 SP - 372 EP - 386 PB - SAGE Publications CY - Sage CA: Los Angeles, CA ER - TY - JOUR A1 - Fekih Hassen, Wiem A1 - Challouf, Maher T1 - Long short-term renewable energy sources prediction for grid-management systems based on stacking ensemble model JF - Energies N2 - The transition towards sustainable energy systems necessitates effective management of renewable energy sources alongside conventional grid infrastructure. This paper presents a comprehensive approach to optimizing grid management by integrating Photovoltaic (PV), wind, and grid energies to minimize costs and enhance sustainability. A key focus lies in developing an accurate scheduling algorithm utilizing Mixed Integer Programming (MIP), enabling dynamic allocation of energy resources to meet demand while minimizing reliance on cost-intensive grid energy. An ensemble learning technique, specifically a stacking algorithm, is employed to construct a robust forecasting pipeline for PV and wind energy generation. The forecasting model achieves remarkable accuracy with a Root Mean Squared Error (RMSE) of less than 0.1 for short-term (15 min and one day ahead) and long-term (one week and one month ahead) predictions. By combining optimization and forecasting methodologies, this research contributes to advancing grid management systems capable of harnessing renewable energy sources efficiently, thus facilitating cost savings and fostering sustainability in the energy sector. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-14649 VL - 2024 IS - 17(13) ER - TY - JOUR A1 - Bleyer, Bernhard A1 - Zink, Roland T1 - Sustainable Development Goals und ihre Orientierungsfunktion für angewandte Wissenschaften T1 - Sustainable Development Goals and their guidance function for applied sciences JF - Bavarian Journal of Applied Science N2 - Editorial des Bavarian Journal of Applied Science 5 KW - Sustainable development goals KW - nachhaltige Entwicklung Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-14372 VL - 2019 IS - 5 SP - 406 EP - 411 CY - Deggendorf ER - TY - JOUR A1 - Adiatu, Afeez T1 - Energizing the inter-regional cooperation and energy governance : an exploration of the Africa-EU energy partnership JF - Journal of Sustainable Development of Energy, Water and Environment Systems (ISSN: 1848-9257, DOI: 10.13044/j.sdewes) N2 - The emergence of change in the global energy governance structure is precipitated by the shift in global energy technology. The shift from carbon-intense energy to cleaner sources surpasses technological discontinuation. The inter-regional, regional, and sub-regional grouping emerged in global energy governance to support governance capabilities across countries. This research seeks to investigate the inter-regional partnership between Africa and the European Union initiated to facilitate energy decision-making. This study adopts thematic analysis to explore literature and reports on the Africa-EU partnership to understand its impact on the future of the African energy sector. This research argues using a neo-liberal lens that the limited state capacity in energy governance may necessitate inter-regional partnerships to aid energy sector development in Africa. The study concludes that considering Africa's potential in renewable energy sources such as solar irradiation and the limited energy access in the Sub-Saharan region, intervention of external capabilities through technological and financial aids may stimulate the utilization of such potential. KW - global energy governance KW - renewable energy KW - energy transition KW - regionalism KW - global governance Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15782 VL - 2024 IS - 12(4) PB - SDEWES Centre CY - Zagreb ER - TY - JOUR A1 - Schmid-Petri, Hannah A1 - Elschner, Sophie G. T1 - Transitionalists, traditionalists or pioneers? How German municipal energy companies are responding to the national energy transition JF - Energy Research & Social Science (Online ISSN: 2214-6326) N2 - The Renewable Energy Sources Act (EEG) in Germany aims to transition the country to a sustainable energy system. This has led to a decentralization of the energy market and a shift toward community-focused energy supply systems. Municipal energy companies (MECs), deeply rooted in their communities, are crucial in facilitating this transition and promoting innovative technologies. Websites serve as important communication tools, facilitating interaction between companies and consumers. In our study, we conducted a quantitative content analysis to examine how MECs communicate issues related to the energy transition on their web pages (N = 300). In general, our results show that the energy transition was rarely mentioned on landing pages, and while companies are improving their sustainable electricity products, renewable gas and heating tariffs have received little attention. Additionally, we identified three communication types of MECs: The transitionalists (45 %), the traditionalists (35 %), and the pioneers (20 %), with the latter being the most innovative that emphasizes issues related to the energy transition. Overall, it can be said that the MECs have not yet fully exploited their potential to position themselves as pioneers of the energy transition in their website communications. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-18714 VL - 2024 IS - 109 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Otto, Alena A1 - Tilk, Christian T1 - Intelligent design of sensor networks for data-driven sensor maintenance at railways JF - Omega (Online ISSN: 1873-5274) N2 - With rapid advances in digitization, many critical processes in transportation, industries, and our daily life rely on sensor measurements. With time, however, the measurements may get gradually biased and their precision deteriorates, leading to an enhanced risk of major disruptions caused by false sensor measurements. All single sensor measurements are uncertain and deviate from the true value. To detect malfunctioning sensors early on, a set of recent measurements of each sensor has to be constantly cross-checked against the measurements of a given number of other sensors, i.e., sensors should form a diagnosable network. In this article, we examine the intelligent positioning of safety-relevant sensors at railways such that the installed sensors can constantly cross-check each other and the number of the required sensors is minimized. The arising sensor positioning problem (SPP) belongs to the family of the coordinated set covering problems with two binary matrices: the choice of columns in one matrix implies the selection of specific columns and rows in the other matrix. We formulate an integer program, provide some formal analysis of the SPP and design a customized large neighborhood search metaheuristic RuM, which finds close-to-optimality solutions fast. In our computational experiments, we show that if we ignore the diagnosability requirement, the installed sensors cannot sufficiently cross-check each other in most cases. However, it costs only a few (or even no) additional sensors to ensure the diagnosability of the sensor network. KW - Rail transport KW - Integer programming KW - Sensors KW - Set covering problem KW - Network design KW - Diagnosable network Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-18771 VL - 2024 IS - 127 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Fekih Hassen, Wiem A1 - Schoppik, Luis A1 - Schiegg, Sascha A1 - Gerl, Armin T1 - Power management approach of hybrid energy storage system for electric vehicle charging stations JF - Smart Cities N2 - The applicability of Hybrid Energy Storage Systems (HESSs) has been shown in multiple application fields, such as Charging Stations (CSs), grid services, and microgrids. HESSs consist of an integration of two or more single Energy Storage Systems (ESSs) to combine the benefits of each ESS and improve the overall system performance. In this work, we propose a novel power management controller called the Hybrid Controller for the efficient HESS’s charging and discharging, considering the State of Charge (SoC) of the HESS and the dynamic supply and load. The Hybrid Controller optimises the use of the HESS, i.e., minimises the amount of energy drawn from and discharged to the grid, thus utilising and prioritising the provided Photovoltaic (PV) power. The performance of our proposal was assessed via simulation using various evaluation metrics, i.e., Autarky, charge/discharge cycle, and Self-Consumption (SC), where we defined 24 scenarios in different locations in Germany. KW - HESS KW - RFB KW - lithium battery KW - power distribution KW - OpenEMS KW - real load dataset Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:m347-opus-6045 SN - 2624-6511 VL - 7 (2024) IS - 6 SP - 4025 EP - 4051 PB - MDPI CY - Basel ER - TY - JOUR A1 - Hackl, Veronika A1 - Müller, Alexandra Elena A1 - Granitzer, Michael A1 - Sailer, Maximilian T1 - Is GPT-4 a reliable rater? Evaluating consistency in GPT-4's text ratings JF - Frontiers in Education N2 - This study reports the Intraclass Correlation Coefficients of feedback ratings produced by OpenAI's GPT-4, a large language model (LLM), across various iterations, time frames, and stylistic variations. The model was used to rate responses to tasks related to macroeconomics in higher education (HE), based on their content and style. Statistical analysis was performed to determine the absolute agreement and consistency of ratings in all iterations, and the correlation between the ratings in terms of content and style. The findings revealed high interrater reliability, with ICC scores ranging from 0.94 to 0.99 for different time periods, indicating that GPT-4 is capable of producing consistent ratings. The prompt used in this study is also presented and explained. KW - artificial intelligence KW - GPT-4 KW - large language model KW - prompt engineering KW - feedback KW - higher education Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-18348 SN - 2504-284X VL - 2023 IS - 8 PB - Frontiers CY - Lausanne ER -