Publikationsserver der Ostbayerischen Technischen Hochschule Regensburg
Not a member yet
6172 research outputs found
Sort by
SAT Strikes Back: Parameter and Path Relations in Quantum Toolchains
No full textIn the foreseeable future, toolchains for quantum computing should offer automatic means of transforming a high level problem formulation down to a hardware executable form. Thereby, it is crucial to find (multiple) transformation paths that are optimised for (hardware specific) metrics. We zoom into this pictured tree of transformations by focussing on k-SAT instances as input and their transformation to QUBO, while considering structure and characteristic metrics of input, intermediate and output representations. Our results can be used to rate valid paths of transformation in advance—also in automated (quantum) toolchains. We support the automation aspect by considering stability and therefore predictability of free parameters and transformation paths. Moreover, our findings can be used in the manifesting era of error correction (since considering structure in a high abstraction layer can benefit error correcting codes in layers below). We also show that current research is closely linked to quadratisation techniques and their mathematical foundation
Ein strukturierter Vergleich ausgewählter Process Mining Tools
No full textDie Notwendigkeit zur Optimierung und Automatisierung von Ablaufen in Unternehmen nimmt mit zunehmender Digitalisierung an Fahrt auf. Zur Unterstützung dieses Trends haben sich in den letzten Jahren einige Tools im Themenbereich Process Mining entwickelt und etabliert.
Ziel dieser Untersuchung ist es, systematisch ausgewählte Tools anhand eines vorhandenen, aber weiterentwickelten Kriterienkatalogs zu vergleichen und damit dem Anwender eine strukturierte Einsicht in den aktuellen Markt der Process Mining Tools zu geben. Aus einer Auswahl von 44 Tools werden acht Tools genauer untersucht. Die letztendliche Auswahl hängt von vielen unternehmensindividuellen Faktoren ab, so dass kein pauschaler Vorschlag für das geeignetste Tool gegeben werden kann
Predicting intra-abdominal pressure during walking and running
No full textIntra-abdominal pressure (IAP) is an important physiological parameter, which is difficult to measure during physical activity. In this study, motion capture, musculoskeletal modeling and a transformer encoder model are used to predict IAP during walking and running. The model showed promising results with an overall mean percentage error of 13.5% and a Pearson correlation coefficient of 0.85. Minor challenges included the lower accuracy for fast walking and running and the limited amount of data. All in all, the prediction of IAP was successful, which opens up prospects for further applications
Recording and understanding multi- and intermodal mobility - a review
No full textThe transition to sustainable mobility requires detailed knowledge of actual mobility behavior. Recording mobility behavior through conventional, aggregated, or retrospective survey methods (e.g., counting stations, travel diaries) may yield incomplete insights. In addition, these methods are often expensive, prone to error, or not scalable. The aim of this literature review is to provide a systematic overview of the current state of the literature on recording and analysis of individual mobility data and, based on this, to identify possible research gaps and potential. The exploratory literature review includes social science surveys on multi- and intermodal mobility behavior, as well as an overview of possible ways to analyze travel data. The focus of the latter is on identifying relevant data sources and methodological approaches
for segmentation, identification of transport mode, and trip purpose determination.
Results from recent studies show that sensor-based data collection alone is not sufficient to fully and accurately map mobility behavior. One possible solution is a “best-of-both-worlds” approach that combines passive, automatic mobility data collection via smartphone sensors with targeted user corrections and additions (“human-in-the-loop”) within an app. The literature review shows that this approach yields the best data quality. Combining mobility surveys with passive collection of mobility data provides a comprehensive, accurate, and complete overview of mobility behavior
Harvesting Sustainability: Cost-competitiveness of Green Fertilizer Value Chains in Western Africa
No full textThe use of nitrogen fertilizers in Sub-Saharan Africa is low compared to other regions of the world, leading to inadequate crop yields. Furthermore, conventional production from fossil fuel-based ammonia is highly emissions-intensive, making decarbonization urgent. Local production using green hydrogen, sourced solely from solar energy, water, and air, could address both agricultural and climate challenges. This study focuses on Ghana, where nitrogen inputs are among the lowest globally. Using an open-source framework, we evaluate high-resolution production costs for sustainable ammonia and examine two decarbonized pathways: aqueous ammonia and urea. It is found that cost estimates with current assumptions mostly exceed historical prices. However, given their resilience to global market disruptions and expected future cost decreases of the technologies used, these sustainable approaches represent a promising pathway for development in Sub-Saharan Africa
Generative KI: Vom technologischen Paradigmenwechsel zur Vision einer neuen Ära im Straßenverkehr
No full textGenerative Künstliche Intelligenz (KI) geht bereits mit enormen Effizienzsteigerungen für Domänen einher, die von Kreativität profitieren. Die Fähigkeit, beliebig viele realitätsnahe Daten zu synthetisieren, bietet jedoch auch neue Potenziale für Anwendungen, die bisher aufgrund fehlender Datenmengen noch nicht den Sprung in die Praxis überwunden haben. Im Straßenverkehr betrifft dies z. B. das autonome Fahren in herausfordernden Situationen. Um neue Anwendungspotenziale zu erschließen, ist es allerdings erforderlich, die grundlegende Funktionsweise der Technologie gepaart mit ihren Chancen und Herausforderungen zu verstehen. Dieser Fachbeitrag dient deshalb als erste Einführung in die generative KI, indem er einen Überblick über zentrale Modelle, ihre grundlegenden Ideen und Funktionsweisen gibt. Darauf basierend werden typische Problemarten aufgezeigt, die mit generativer KI neu betrachtet und besser gelöst werden können – allgemein und spezifisch für den Straßenverkehr. Unter gleichzeitiger Betrachtung derzeitiger Limitierungen dient der Beitrag als Entscheidungshilfe für die Selektion passender generativer oder klassischer KI-Verfahren.Generative artificial intelligence (AI) is associated with enormous increases in efficiency for domains that benefit from creativity. However, the ability to synthesize any amount of realistic data also offers new potential for applications that have not yet made the leap into practice due to a lack of data. In road traffic, for example, this applies to autonomous driving in challenging situations. However, in order to unlock new application potential, it is necessary to understand the basic functioning of the technology coupled with its opportunities and challenges. This article therefore serves as a gentle introduction to generative AI by providing an overview of central models, their fundamental ideas and function. Based on this, we present typical problem types that can be revisited and profit from generative AI – in general and specifically for road traffic. While at the same time considering current limitations, the article serves as a decision support for the selection of suitable generative or classic AI methods
Large-Scale Multiple Query Optimisation with Incremental Quantum(-Inspired) Annealing
No full textMultiple-query optimization (MQO) seeks to reduce redundant work across query batches. While MQO offers opportunities for dramatic performance improvements, the problem is NP-hard, limiting the sizes of problems that can be solved on generic hardware. We propose to leverage specialized hardware solvers for optimization, such as Fujitsu's Digital Annealer (DA), to scale up MQO to problem sizes formerly out of reach.
We present a novel incremental processing approach that combines classical computation with DA acceleration. By efficiently partitioning MQO problems into sets of partial problems, and by applying a dynamic search steering strategy that reapplies initially discarded information to incrementally process individual problems, our method overcomes capacity limitations, and scales to extremely large MQO instances (up to νm1000 queries). A thorough and comprehensive empirical evaluation finds our method substantially outperforms existing approaches. Our generalisable framework lays the ground for other database use-cases on quantum-inspired hardware, and bridges towards future quantum accelerators
Multi-Day Scheduling for Electric Vehicle Routing: A Novel Model and Comparison Of Metaheuristics
No full textThe increasing use of electric vehicles (EVs) requires efficient route planning solutions that take into account the limited range of EVs and the associated charging times, as well as the different types of charging stations. In this work, we model and solve an electric vehicle routing problem (EVRP) designed for a cross-platform navigation system for individual transport. The aim is to provide users with an efficient route for their daily appointments and to reduce possible inconveniences caused by charging their EV. Based on these assumptions, we propose a multi-day model in the form of a mixed integer programming (MIP) problem that takes into account the vehicle's battery capacity and the time windows of user's appointments.
The model is solved using various established metaheuristics, including tabu search (TS), adaptive large neighborhood search (ALNS), and ant colony optimization (ACO). Furthermore, the performance of the individual approaches is analyzed using generated ensembles to estimate their behavior in reality and is compared with the exact results of the Google OR-Tools solver.
6 pages, 5 figure
Impacts of lifestyle changes on energy demand and greenhouse gas emissions in Germany
No full textMost energy scenario studies typically focus on technological options and fuel substitution for decarbonising future energy systems. Lifestyle changes are rarely considered, although they can significantly reduce energy demand and climate change mitigation efforts. By using an energy system model, this study shows that it is possible to reduce final energy demand in Germany by 61 % in 2050 relative to 2019 levels, resulting in an annual per capita energy demand of 44 GJ for a representative country of the Global North. This goal can be achieved through a combination of technological measures and lifestyle changes without sacrificing a decent standard of living. Societal chances can eliminate reliance on not-yet-established negative emission technologies, reduce energy dependency, and reduce the need for energy-intensive hydrogen and e-fuels. Downsizing the energy system provides an opportunity for strengthening climate change mitigation, decrease material demand and reduce land use
Sustainable Steel Production in the Desert: Economic and Technical Assessment of a Hydrogen-Powered Steel Plant in Mauritania
No full textThe global steel industry is a major contributor to climate change and faces challenges in achieving a carbon-neutral production, hinging on the availability of cost-effective hydrogen produced by renewable energy. Mauritania, with its exceptional solar and wind resources, offers some of the most competitive conditions globally for hydrogen production. Instead of focusing on hydrogen exports, this study explores the technical feasibility and economic viability of establishing a renewable-powered steel plant in Mauritania, utilizing the country’s abundant iron ore reserves. The findings suggest that sustainably produced steel in Mauritania could be cost-competitive with current European prices. With ongoing declines in investment costs for emerging renewable technologies, Mauritania has the potential to become one of the world’s most cost-effective steel producers