University of Applied Sciences Emden Leer
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509 research outputs found
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Educational Concept and Application of Problem-Based Learning Using a Virtual Learning Factory
No full textThe COVID-19 pandemic affected the common ways of teaching students, and new formats for lectures and exams are required. The paper presents a new lecture concept that combines problem-based learning and a virtual learning factory. The virtual learning factory offers a digital production system which offers several opportunities to collect and analyze production data. The students can use the data to solve their selected problems. The new lecture concept was applied and evaluated in the lecture “simulation of energy systems.” The paper concludes with a discussion of the students’ evaluation results and lecturers´ experiences
RESTful information-centric networking: statement
No full textWeb applications today utilize the Representation State Transfer (REST) architectural pattern, depending on HTTP, TLS, and either TCP or QUIC as the protocol substrate to build upon. Our vision is to achieve the key properties of REST using ICN protocols as an alternative. We argue that this is feasible given some of the recent advances in ICN protocol development and that the resulting suite is simpler and potentially having better performance and robustness properties. Our sketch of an ICN-based protocol framework addresses secure and efficient establishment and continuation of REST communication sessions, without giving up key ICN properties, such as consumer anonymity and flow balance
Robo-advisors as part of industry 4.0 in financial markets: Evolutionary development, methods, and first performance insights
No full textToday, an essential disruptive trend of the fourth industrial revolution is robo-advisors that offer innovative asset management services (Tao, Su, Xiao, Dai, & Khalid, 2021). They are automated investment platforms that use quantitative algorithms to produce advice to investors to help them manage their portfolios and are accessible to clients online (Beketov, Lehmann, & Wittke, 2018). Until now, there has been no comprehensive analysis of the development of these innovative advisors, the asset allocation methods used, and the performance (also concerning the Corona crisis). Thus, the paper takes robo-advisory-related research a step further by analyzing the development of robo-advisory on a global scale from an evolutionary point of view, at the same time focusing on the variety of methods applied by the advisors and the factors influencing their performance between 2018 and 2021 by regression analysis. Our results show that modern portfolio theory remains the primary framework used by robo-advisors, even though some use new approaches. The average performance of robo-advisors appears to beat the market benchmark, however not significantly during the Corona-crash period. Important factors influencing their performance are the number of allocation methods applied and, specifically, the technique of rebalancing. The findings demonstrate that in the context of Industry 4.0, robo-advisors can offer advantages not only in terms of costs and technical processes but also in terms of performance
An Open Source Grid Observer for the Analysis of Power Flexibilities in Low Voltage Distribution Grid Simulations
No full textThe existence of voltage range violations represents a challenge in low voltage grids with a high penetration of decentralized generation, storage capacities or electro-mobility. If grid expansion is to be avoided in the future, an extensive information exchange between the system’s components is required to provide an optimal energy supply and guarantee operating requirements. This can be studied in details by modelling the energy system components and the communication between them, which is one of the aims of the research project "Future Energy Laboratories". Highly integrated application scenarios for sample districts in Germany are simulated and thoroughly analysed during the project. For the detection and correction of voltage range violations at individual buses of a grid, an Open Source Grid Observer tool was developed and tested as a flexibility feature in a quasi-dynamic energy system simulation of a residential district. It allows a wide range of compatibility between various simulation scenarios, as it gives recommendations for power control at considered buses according to predefined flexibilities, such as the type of power (active or reactive), flexibility components (e.g. generation and storage) and injection increment. The corrections were calculated using two methods of the voltage sensitivity analysis theory. A comparison between the methods’ robustness, accuracy and calculation speed is presented, being important performance factors to be considered in this kind of simulations. The functionality of the tool is demonstrated in scenarios with temporary peak loads from electric vehicle charging or a high share of distributed photovoltaic power generation
Microbiome Analysis via OTU and ASV-Based Pipelines—A Comparative Interpretation of Ecological Data in WWTP Systems
No full textLinking community composition and ecosystem function via the cultivation-independent analysis of marker genes, e.g., the 16S rRNA gene, is a staple of microbial ecology and dependent disciplines. The certainty of results, independent of the bioinformatic handling, is imperative for any advances made within the field. In this work, thermophilic anaerobic co-digestion experimental data, together with primary and waste-activated sludge prokaryotic community data, were analyzed with two pipelines that apply different principles when dealing with technical, sequencing, and PCR biases. One pipeline (VSEARCH) employs clustering methods, generating individual operational taxonomic units (OTUs), while the other (DADA2) is based on sequencing error correction algorithms and generates exact amplicon sequence variants (ASVs). The outcomes of both pipelines were compared within the framework of ecological-driven data analysis. Both pipelines provided comparable results that would generally allow for the same interpretations. Yet, the two approaches also delivered community compositions that differed between 6.75% and 10.81% between pipelines. Inconsistencies were also observed linked to biologically driven variability in the samples, which affected the two pipelines differently. These pipeline-dependent differences in taxonomic assignment could lead to different conclusions and interfere with any downstream analysis made for such mis- or not-identified species, e.g., network analysis or predictions of their respective ecosystem service
Blockchain: What Does It Mean to Industrial Electronics?: Technologies, Challenges, and Opportunities
No full textExtraction and Analysis of Highway On-Ramp Merging Scenarios from Naturalistic Trajectory Data
No full textAutomated Vehicles are envisioned to transform the future industrial and private transportation sectors. However, due to the system's enormous complexity, functional verification and validation of safety aspects are essential before the technology merges into the public domain. In recent years, a scenario-driven approach has gained acceptance, emphasizing the requirement of a solid data basis of scenarios. The large-scale research facility Test Bed Lower Saxony (TFNDS) of the German Aerospace Center (DLR) enables the provision of ample information for a database of scenarios on highways. For that purpose, however, the scenarios of interest must be identified and extracted from the collected Naturalistic Trajectory Data (NTD). This work addresses this problem and proposes a methodology for on-ramp scenario extraction, enabling scenario categorization and assessment. A Hidden Markov Model and Dynamic Time Warping is utilized for extraction and a decision tree with the Surrogate Measure of Safety Post Encroachment Time for categorization and assessment. The efficacy of the approach is shown with a dataset of NTD collected on the TFNDS
Epilog. Erkenntnisse und Perspektiven für gesellschaftlich wahrgenommene Ausnahmesituationen
No full textDelay-tolerant ICN and its application to LoRa
No full textConnecting long-range wireless networks to the Internet imposes challenges due to vastly longer round-trip-times (RTTs). In this paper, we present an ICN protocol framework that enables robust and efficient delay-tolerant communication to edge networks. Our approach provides ICN-idiomatic communication between networks with vastly different RTTs. We applied this framework to LoRa, enabling end-to-end consumer-to-LoRa-producer interaction over an ICN-Internet and asynchronous data production in the LoRa edge. Instead of using LoRaWAN, we implemented an IEEE 802.15.4e DSME MAC layer on top of the LoRa PHY and ICN protocol mechanisms in RIOT OS. Executed on off-the-shelf IoT hardware, we provide a comparative evaluation for basic NDN-style ICN [60], RICE [31]-like pulling, and reflexive forwarding [46]. This is the first practical evaluation of ICN over LoRa using a reliable MAC. Our results show that periodic polling in NDN works inefficiently when facing long and differing RTTs. RICE reduces polling overhead and exploits gateway knowledge, without violating ICN principles. Reflexive forwarding reflects sporadic data generation naturally. Combined with a local data push, it operates efficiently and enables lifetimes of ≥1 year for battery powered LoRa-ICN nodes