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Training and evaluating deep learning models on road graphs for traffic prediction using SUMO
(2024)
The escalation of traffic volume in urban areas poses multifaceted challenges including increased accident risks, congestion, and prolonged travel times. Traditional approaches of expanding road infrastructure face limitations such as space constraints and the potential exacerbation of traffic issues.
Intelligent Transport Systems (ITS) present an alternative strategy to alleviate traffic problems by leveraging data-driven solutions. Central to ITS is traffic prediction, a process vital for applications like Traffic Management and Navigation Systems.
Recent advancements in traffic prediction have witnessed a surge of interest, particularly in deep learning methods optimized for graph-based data processing, being considered the most promising avenue presently.
These methods typically rely on real-life datasets containing traffic sensor data such as METR-LA and PeMS. However, the finite nature of real-life data prompts exploration into augmenting training and testing datasets with simulated traffic data.
This thesis explores the potential of utilizing traffic simulations, employing the microscopic traffic simulator SUMO, to train and test deep learning models for traffic prediction. A framework integrating PyTorch and SUMO is proposed for this purpose, aiming to elucidate the feasibility and effectiveness of using simulated traffic data for enhancing predictive models in traffic management systems.
The Logical Observation Identifiers, Names and Codes (LOINC) is a common terminology used for standardizing laboratory terms. Within the consortium of the HiGHmed project, LOINC is one of the central terminologies used for health data sharing across all university sites. Therefore, linking the LOINC codes to the site-specific tests and measures is one crucial step to reach this goal. In this work we report our ongoing efforts in implementing LOINC to our laboratory information system and research infrastructure, as well as our challenges and the lessons learned. 407 local terms could be mapped to 376 LOINC codes of which 209 are already available to routine laboratory data. In our experience, mapping of local terms to LOINC is a widely manual and time consuming process for reasons of language and expert knowledge of local laboratory procedures.
The German Corona Consensus (GECCO) established a uniform dataset in FHIR format for exchanging and sharing interoperable COVID-19 patient specific data between health information systems (HIS) for universities. For sharing the COVID-19 information with other locations that use openEHR, the data are to be converted in FHIR format. In this paper, we introduce our solution through a web-tool named “openEHR-to-FHIR” that converts compositions from an openEHR repository and stores in their respective GECCO FHIR profiles. The tool provides a REST web service for ad hoc conversion of openEHR compositions to FHIR profiles.
Renewable energy production is one of the strongest rising markets and further extreme growth can be anticipated due to desire of increased sustainability in many parts of the world. With the rising adoption of renewable power production, such facilities are increasingly attractive targets for cyber attacks. At the same time higher requirements on a reliable production are raised. In this paper we propose a concept that improves monitoring of renewable power plants by detecting anomalous behavior. The system does not only detect an anomaly, it also provides reasoning for the anomaly based on a specific mathematical model of the expected behavior by giving detailed information about various influential factors causing the alert. The set of influential factors can be configured into the system before learning normal behaviour. The concept is based on multidimensional analysis and has been implemented and successfully evaluated on actual data from different providers of wind power plants.
Purpose: Radiology reports mostly contain free-text, which makes it challenging to obtain structured data. Natural language processing (NLP) techniques transform free-text reports into machine-readable document vectors that are important for creating reliable, scalable methods for data analysis. The aim of this study is to classify unstructured radiograph reports according to fractures of the distal fibula and to find the best text mining method.
Materials & Methods: We established a novel German language report dataset: a designated search engine was used to identify radiographs of the ankle and the reports were manually labeled according to fractures of the distal fibula. This data was used to establish a machine learning pipeline, which implemented the text representation methods bag-of-words (BOW), term frequency-inverse document frequency (TF-IDF), principal component analysis (PCA), non-negative matrix factorization (NMF), latent Dirichlet allocation (LDA), and document embedding (doc2vec). The extracted document vectors were used to train neural networks (NN), support vector machines (SVM), and logistic regression (LR) to recognize distal fibula fractures. The results were compared via cross-tabulations of the accuracy (acc) and area under the curve (AUC).
Results: In total, 3268 radiograph reports were included, of which 1076 described a fracture of the distal fibula. Comparison of the text representation methods showed that BOW achieved the best results (AUC = 0.98; acc = 0.97), followed by TF-IDF (AUC = 0.97; acc = 0.96), NMF (AUC = 0.93; acc = 0.92), PCA (AUC = 0.92; acc = 0.9), LDA (AUC = 0.91; acc = 0.89) and doc2vec (AUC = 0.9; acc = 0.88). When comparing the different classifiers, NN (AUC = 0,91) proved to be superior to SVM (AUC = 0,87) and LR (AUC = 0,85).
Conclusion: An automated classification of unstructured reports of radiographs of the ankle can reliably detect findings of fractures of the distal fibula. A particularly suitable feature extraction method is the BOW model.
Key Points:
- The aim was to classify unstructured radiograph reports according to distal fibula fractures.
- Our automated classification system can reliably detect fractures of the distal fibula.
- A particularly suitable feature extraction method is the BOW model.
The Wnt signaling pathway has been associated with many essential cell processes. This study aims to examine the effects of Wnt signaling on proliferation of cultured HEK293T cells. Cells were incubated with Wnt3a, and the activation of the Wnt pathway was followed by analysis of the level of the β-catenin protein and of the expression levels of the target genes MYC and CCND1. The level of β-catenin protein increased up to fourfold. While the mRNA levels of c-Myc and cyclin D1 increased slightly, the protein levels increased up to a factor of 1.5. Remarkably, MTT and BrdU assays showed different results when measuring the proliferation rate of Wnt3a stimulated HEK293T cells. In the BrdU assays an increase of the proliferation rate could be detected, which correlated to the applied Wnt3a concentration. Oppositely, this correlation could not be shown in the MTT assays. The MTT results, which are based on the mitochondrial activity, were confirmed by analysis of the succinate dehydrogenase complex by immunofluorescence and by western blotting. Taken together, our study shows that Wnt3a activates proliferation of HEK293 cells. These effects can be detected by measuring DNA synthesis rather than by measuring changes of mitochondrial activity.
In industrial production facilities, technical Energy Management Systems are used to measure, monitor and display energy consumption related information. The measurements take place at the field device level of the automation pyramid. The measured values are recorded and processed at the control level. The functionalities to monitor and display energy data are located at the MES level of the automation pyramid. So the energy data from all PLCs has to be aggregated, structured and provided for higher level systems. This contribution introduces a concept for an Energy Data Aggregation Layer, which provides the functionality described above. For the implementation of this Energy Data Aggregation Layer, a combination of AutomationML and OPC UA is used.
Integrated Risk and Opportunity Management (IROM) goes far beyond what is found in organizations today. However, it offers the best opportunity not only to keep pace with the VUCA world, but to actually profit from it. Accordingly, the introduction of opportunity-based thinking in addition to risk-based thinking is part of the design specification for ISO 9000 and ISO 9001. The prerequisite for the successful design of an IROM is the individual definition, control and integration of risk and opportunity management processes, considering eight success factors, the "8 C". Top management benefits directly from the result: better, coordinated decision memos enable faster and more appropriate decisions.
Ein Integriertes Risiko- und Chancenmanagement (IRCM) geht deutlich über das hinaus, was in den Organisationen heute anzutreffen ist. Es bietet jedoch die beste Möglichkeit, nicht nur mit der VUKA-Welt Schritt zu halten, sondern sogar von ihr zu profitieren. Entsprechend ist die Einführung eines chancenbasierten Denkens in Ergänzung zum risikobasierten Denken Bestandteil der Revisionsagenda für die ISO 9000 und 9001. Voraussetzung für die erfolgreiche Gestaltung eines IRCM ist die individuelle Definition, Steuerung und Integration von Risiko- und Chancenmanagementprozessen unter Beachtung von 8 Erfolgsfaktoren, den „8K“. Vom Ergebnis profitiert das Top-Management direkt: Bessere, abgestimmte Entscheidungsvorlagen ermöglichen schnellere, sachgerechtere Entscheidungen.
Harmonisation of German Health Care Data Using the OMOP Common Data Model – A Practice Report
(2023)
Data harmonization is an important step in large-scale data analysis and for generating evidence on real world data in healthcare. With the OMOP common data model, a relevant instrument for data harmonization is available that is being promoted by different networks and communities. At the Hannover Medical School (MHH) in Germany, an Enterprise Clinical Research Data Warehouse (ECRDW) is established and harmonization of that data source is the focus of this work. We present MHH’s first implementation of the OMOP common data model on top of the ECRDW data source and demonstrate the challenges concerning the mapping of German healthcare terminologies to a standardized format.
Betreiber von Produktionsanlagen stehen oft vor der Frage, welche Norm für die Absicherung der Anlage gegen Cyberangriffe heranzuziehen ist. Aus dem IT-Bereich ist die Normreihe ISO 27000 bekannt. Im Produktionsbereich wird häufig die Normreihe IEC 62443 herangezogen. Dieser Beitrag gibt einen Überblick über beide Normreihen und schlägt einen Ansatz zur gemeinsamen Nutzung beider Standards vor.
Bürstenlose Generatorsysteme mit doppelt gespeisten Kaskadenmaschinen werden zurzeit für die regenerative Energieerzeugung z. B. mit Windkraftanlagen untersucht. Sie sind eine Alternative zu Generatorsystemen mit doppelt gespeisten Induktionsmaschinen. Kaskadenmaschinen arbeiten mit zwei Drehfeldern verschiedener Polpaarzahl. Im Stator befinden sich zwei Wicklungen für die beiden Polpaarzahlen oder eine Wicklung zur gleichzeitigen Erzeugung der beiden Drehfelder mit getrennten Anschlüssen für die beiden Drehfelder. Der Rotor trägt eine in sich kurzgeschlossene Wicklung, die gleichzeitig mit beiden Drehfeldern verkettet ist und deren Strom beide Drehfelder gleichzeitig erzeugt. Der vorliegende Beitrag beschreibt wie die elektromagnetischeWirkung unsymmetrischer Rotorwicklungen für Kaskadenmaschinen mit der Drehfeldanalyse behandelt werden kann. Die Rotorwicklungen dienen dazu, gleichzeitig beide Grundfelder der Kaskadenmaschine zu erzeugen. Dazu sind sie z. T. mit Wicklungszweigen aufgebaut, die in verschiedenen Knoten zusammen geschaltet sind. Aus Sicht der Statorwicklungen sind sie unsymmetrisch aufgebaut. Unsymmetrische Rotorwicklungen treten auch in Induktions- und Synchronmaschinen auf, z. B. bei Wicklungsfehlern, Stabbrüchen oder bei unsymmetrischen Anlaufkäfigen. Mit dem hier dargestellten Rechenverfahren wird die elektromagnetische Kopplung zwischen den Wicklungszweigen und zur Statorwicklung erfasst.
Diese Arbeit thematisiert die unausgeschöpften Potentiale der von Designer*innen erzeugten Formen. Um zu klären, welche Wichtigkeit der Formfindung innerhalb des gestalterischen Prozesses zukommt, wird die Form mit anderen Parametern der Gestaltung verglichen. Es wird untersucht, welche Wirkungen die Formen auf Menschen haben können, die mit ihnen interagieren wollen oder müssen. Auf der Suche nach Möglichkeiten, die so ermittelten Potentiale freizuschalten, wird der bisher begrenzende Rahmen betrachtet. In einem phänomenologischen Versuch wird geprüft, welche Mannigfaltigkeit von dem generativen Prozess einer künstlichen Intelligenz vorgeschlagen werden kann. Das Ergebnis sind verschobene Grenzen, die zahlreiche Felder der Formausprägung zu einem Größeren erschließen. Eine absolute Entgrenzung des Formendenkens muss derweil scheitern.
Autonomous and integrated passenger and freight transport (APFIT) is a promising approach to tackle both, traffic and last-mile-related issues such as environmental emissions, social and spatial conflicts or operational inefficiencies. By conducting an agent-based simulation, we shed light on this widely unexplored research topic and provide first indications regarding influential target figures of such a system in the rural area of Sarstedt, Germany. Our results show that larger fleets entail inefficiencies due to suboptimal utilization of monetary and material resources and increase traffic volume while higher amounts of unused vehicles may exacerbate spatial conflicts. Nevertheless, to fit the given demand within our study area, a comparatively large fleet of about 25 vehicles is necessary to provide reliable service, assuming maximum passenger waiting times of six minutes to the expense of higher standby times, rebalancing effort, and higher costs for vehicle acquisition and maintenance.
The NOA project collects and stores images from open access publications and makes them findable and reusable. During the project a focus group workshop was held to determine whether the development is addressing researchers’ needs. This took place before the second half of the project so that the results could be considered for further development since addressing users’ needs is a big part of the project. The focus was to find out what content and functionality they expect from image repositories.
In a first step, participants were asked to fill out a survey about their images use. Secondly, they tested different use cases on the live system. The first finding is that users have a need for finding scholarly images but it is not a routine task and they often do not know any image repositories. This is another reason for repositories to become more open and reach users by integrating with other content providers. The second finding is that users paid attention to image licenses but struggled to find and interpret them while also being unsure how to cite images. In general, there is a high demand for reusing scholarly images but the existing infrastructure has room to improve.
Bürstenlose Generatorsysteme mit doppelt gespeisten Kaskadenmaschinen werden zzt. für die regenerative Energieerzeugung z. B. mit Windkraftanlagen untersucht. Sie sind eine Alternative zu Generatorsystemen mit doppelt gespeisten Induktionsmaschinen. Kaskadenmaschinen arbeiten mit zwei Drehfeldern verschiedener Polpaarzahl. Im Stator befinden sich zwei Wicklungen für die beiden Polpaarzahlen oder eine Wicklung zur gleichzeitigen Erzeugung der beiden Drehfelder mit getrennten Anschlüssen für die beiden Drehfelder. Der Rotor trägt eine in sich kurzgeschlossene Wicklung, die gleichzeitig mit beiden Drehfeldern verkettet ist und deren Strom beide Drehfelder gleichzeitig erzeugt. Dieser Bericht behandelt die Flussdichte- und Durchflutungsverhältnisse der Wicklungen in Stator und Rotor für Kaskadenmaschinen. Dazu werden die Durchflutungen der Statorwicklungen und der Rotorwicklung für die beiden Polpaarzahlen bestimmt und die für die Wicklungsverluste wirksame Gesamtdurchflutung für verschiedene Polzahlkombinationen ermittelt. Die Ergebnisse werden mit Induktionsmaschinen für eine Polzahl verglichen.
Die vorliegende Bachelorarbeit untersucht Onboarding-Prozesse wissenschaftlicher Bibliotheken, insbesondere anhand einer Analyse der Universitätsbibliothek der Friedrich-Alexander-Universität Erlangen-Nürnberg. Im ersten Teil werden organisationstheoretische und interdisziplinäre Grundlagen beleuchtet. Dabei liegt ein Fokus auf den Herausforderungen, Nutzen und Zielen von Onboarding-Maßnahmen in Abhängigkeit ihres Zeitpunktes und der Zielgruppe. Im Praxisteil werden die gewonnenen Erkenntnisse auf die spezifischen Anforderungen von wissenschaftlichen Bibliotheken angewendet. Die Analyse von Onboarding-Prozessen der Universitätsbibliothek der Friedrich-Alexander-Universität Erlangen-Nürnberg beinhaltet eine Mitarbeitendenbefragung von Onboardees und beteiligten Personen. Die Ergebnisse werden nach der SWOT-Methode eingeordnet. Anschließend folgen Konzepte zur Entwicklung von Arbeitsmaterialien, Unterlagen interner Kommunikation und ein Datenbankkonzept.
Schließlich erfolgt eine ableitende Handlungsempfehlung für eine effektive Umsetzung von Onboarding in wissenschaftlichen Bibliotheken. Das Fazit fasst die wichtigsten Erkenntnisse zusammen, während der Anhang alle Informationen zu den durchgeführten Befragungen, deren Auswertung und die erstellten Arbeitsmaterialien bzw. deren Konzept enthält.
Building a well-founded understanding of the concepts, tasks and limitations of IT in all areas of society is an essential prerequisite for future developments in business and research. This applies in particular to the healthcare sector and medical research, which are affected by the noticeable advances in digitization. In the transfer project “Zukunftslabor Gesundheit” (ZLG), a teaching framework was developed to support the development of further education online courses in order to teach heterogeneous groups of learners independent of location and prior knowledge. The study at hand describes the development and components of the framework.
Powder bed-based additive manufacturing processes offer an extended freedom in design and enable the processing of metals, ceramics, and polymers with a high level of relative density. The latter is a prevalent measure of process and component quality, which depends on various input variables. A key point in this context is the condition of powder beds. To enhance comprehension of their particle-level formation and facilitate process optimization, simulations based on the Discrete Element Method are increasingly employed in research. To generate qualitatively as well as quantitatively reliable simulation results, an adaptation of the contact model parameterization is necessary. However, current adaptation methods often require the implementation of models that significantly increase computational effort, therefore limiting their applicability. To counteract this obstacle, a sophisticated formula-based adaptation and evaluation method is presented in this research. Additionally, the developed method enables accelerated parameter determination with limited experimental effort. Thus, it represents an integrative component, which supports further research efforts based on the Discrete Element Method by significantly reducing the parameterization effort. The universal nature of deducting this method also allows its adaptation to similar parameterization problems and its implementation in other fields of research.