TY - JOUR A1 - Şahin, Muhittin A1 - Egloffstein, Marc A1 - Bothe, Max A1 - Rohloff, Tobias A1 - Schenk, Nathanael A1 - Schwerer, Florian A1 - Ifenthaler, Dirk T1 - Behavioral Patterns in Enterprise MOOCs at openSAP JF - EMOOCs 2021 Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-517350 SN - 978-3-86956-512-5 VL - 2021 SP - 281 EP - 288 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Özdemir, Paker Doğu A1 - Kurban, Caroline Fell A1 - Pekkan, Zelha Tunç T1 - MOOC-Based Online Instruction BT - A Case Study in Teacher Education JF - EMOOCs 2021 N2 - If taking a flipped learning approach, MOOC content can be used for online pre-class instruction. After which students can put the knowledge they gained from the MOOC into practice either synchronously or asynchronously. This study examined one such, asynchronous, course in teacher education. The course ran with 40 students over 13 weeks from February to May 2020. A case study approach was followed using mixed methods to assess the efficacy of the course. Quantitative data was gathered on achievement of learning outcomes, online engagement, and satisfaction. Qualitative data was gathered via student interviews from which a thematic analysis was undertaken. From a combined analysis of the data, three themes emerged as pertinent to course efficacy: quality and quantity of communication and collaboration; suitability of the MOOC; and significance for career development. Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-516900 SN - 978-3-86956-512-5 VL - 2021 SP - 17 EP - 33 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - THES A1 - Zuo, Zhe T1 - From unstructured to structured: Context-based named entity mining from text T1 - Von unstrukturiert zu strukturiert: Kontextbasierte Gewinnung benannter Entitäten von Text N2 - With recent advances in the area of information extraction, automatically extracting structured information from a vast amount of unstructured textual data becomes an important task, which is infeasible for humans to capture all information manually. Named entities (e.g., persons, organizations, and locations), which are crucial components in texts, are usually the subjects of structured information from textual documents. Therefore, the task of named entity mining receives much attention. It consists of three major subtasks, which are named entity recognition, named entity linking, and relation extraction. These three tasks build up an entire pipeline of a named entity mining system, where each of them has its challenges and can be employed for further applications. As a fundamental task in the natural language processing domain, studies on named entity recognition have a long history, and many existing approaches produce reliable results. The task is aiming to extract mentions of named entities in text and identify their types. Named entity linking recently received much attention with the development of knowledge bases that contain rich information about entities. The goal is to disambiguate mentions of named entities and to link them to the corresponding entries in a knowledge base. Relation extraction, as the final step of named entity mining, is a highly challenging task, which is to extract semantic relations between named entities, e.g., the ownership relation between two companies. In this thesis, we review the state-of-the-art of named entity mining domain in detail, including valuable features, techniques, evaluation methodologies, and so on. Furthermore, we present two of our approaches that focus on the named entity linking and relation extraction tasks separately. To solve the named entity linking task, we propose the entity linking technique, BEL, which operates on a textual range of relevant terms and aggregates decisions from an ensemble of simple classifiers. Each of the classifiers operates on a randomly sampled subset of the above range. In extensive experiments on hand-labeled and benchmark datasets, our approach outperformed state-of-the-art entity linking techniques, both in terms of quality and efficiency. For the task of relation extraction, we focus on extracting a specific group of difficult relation types, business relations between companies. These relations can be used to gain valuable insight into the interactions between companies and perform complex analytics, such as predicting risk or valuating companies. Our semi-supervised strategy can extract business relations between companies based on only a few user-provided seed company pairs. By doing so, we also provide a solution for the problem of determining the direction of asymmetric relations, such as the ownership_of relation. We improve the reliability of the extraction process by using a holistic pattern identification method, which classifies the generated extraction patterns. Our experiments show that we can accurately and reliably extract new entity pairs occurring in the target relation by using as few as five labeled seed pairs. N2 - Mit den jüngsten Fortschritten in den Gebieten der Informationsextraktion wird die automatisierte Extrahierung strukturierter Informationen aus einer unüberschaubaren Menge unstrukturierter Textdaten eine wichtige Aufgabe, deren manuelle Ausführung unzumutbar ist. Benannte Entitäten, (z.B. Personen, Organisationen oder Orte), essentielle Bestandteile in Texten, sind normalerweise der Gegenstand strukturierter Informationen aus Textdokumenten. Daher erhält die Aufgabe der Gewinnung benannter Entitäten viel Aufmerksamkeit. Sie besteht aus drei groen Unteraufgaben, nämlich Erkennung benannter Entitäten, Verbindung benannter Entitäten und Extraktion von Beziehungen. Diese drei Aufgaben zusammen sind der Grundprozess eines Systems zur Gewinnung benannter Entitäten, wobei jede ihre eigene Herausforderung hat und für weitere Anwendungen eingesetzt werden kann. Als ein fundamentaler Aspekt in der Verarbeitung natürlicher Sprache haben Studien zur Erkennung benannter Entitäten eine lange Geschichte, und viele bestehenden Ansätze erbringen verlässliche Ergebnisse. Die Aufgabe zielt darauf ab, Nennungen benannter Entitäten zu extrahieren und ihre Typen zu bestimmen. Verbindung benannter Entitäten hat in letzter Zeit durch die Entwicklung von Wissensdatenbanken, welche reiche Informationen über Entitäten enthalten, viel Aufmerksamkeit erhalten. Das Ziel ist es, Nennungen benannter Entitäten zu unterscheiden und diese mit dazugehörigen Einträgen in einer Wissensdatenbank zu verknüpfen. Der letzte Schritt der Gewinnung benannter Entitäten, die Extraktion von Beziehungen, ist eine stark anspruchsvolle Aufgabe, nämlich die Extraktion semantischer Beziehungen zwischen Entitäten, z.B. die Eigentümerschaft zwischen zwei Firmen. In dieser Doktorarbeit arbeiten wir den aktuellen Stand der Wissenschaft in den Domäne der Gewinnung benannter Entitäten auf, unter anderem wertvolle Eigenschaften und Evaluationsmethoden. Darüberhinaus präsentieren wir zwei Ansätze von uns, die jeweils ihren Fokus auf die Verbindung benannter Entitäten sowie der Aufgaben der Extraktion von Beziehungen legen. Um die Aufgabe der Verbindung benannter Entitäten zu lösen schlagen wir hier die Verbindungstechnik BEL vor, welche auf einer textuellen Bandbreite relevanter Begriffe agiert und Entscheidungen einer Kombination von einfacher Klassifizierer aggregiert. Jeder dieser Klassifizierer arbeitet auf einer zufällig ausgewählten Teilmenge der obigen Bandbreite. In umfangreichen Experimenten mit handannotierten sowie Vergleichsdatensätzen hat unser Ansatz andere Lösungen zur Verbindung benannter Entitäten, die auf dem Stand der aktuellen Technik beruhen, sowie in Bezug auf Qualität als auch Effizienz geschlagen. Für die Aufgabe der Extraktion von Beziehungen fokussieren wir uns auf eine bestimmte Gruppe schwieriger Beziehungstypen, nämlich die Geschäftsbeziehungen zwischen Firmen. Diese Beziehungen können benutzt werden, um wertvolle Erkenntnisse in das Zusammenspiel von Firmen zu gelangen und komplexe Analysen ausführen, beispielsweise die Risikovorhersage oder Bewertung von Firmen. Unsere teilbeaufsichtigte Strategie kann Geschäftsbeziehungen zwischen Firmen anhand nur weniger nutzergegebener Startwerte von Firmenpaaren extrahieren. Dadurch bieten wir auch eine Lösung für das Problem der Richtungserkennung asymmetrischer Beziehungen, beispielsweise der Eigentumsbeziehung. Wir verbessern die Verlässlichkeit des Extraktionsprozesses, indem wir holistische Musteridentifikationsmethoden verwenden, welche die erstellten Extraktionsmuster klassifizieren. Unsere Experimente zeigen, dass wir neue Entitätenpaare akkurat und verlässlich in der Zielbeziehung mit bereits fünf bezeichneten Startpaaren extrahieren können. KW - named entity mining KW - information extraction KW - natural language processing KW - Gewinnung benannter Entitäten KW - Informationsextraktion KW - maschinelle Verarbeitung natürlicher Sprache Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-412576 ER - TY - JOUR A1 - Ziegler, Joceline A1 - Pfitzner, Bjarne A1 - Schulz, Heinrich A1 - Saalbach, Axel A1 - Arnrich, Bert T1 - Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-ray Data JF - Sensors N2 - Privacy regulations and the physical distribution of heterogeneous data are often primary concerns for the development of deep learning models in a medical context. This paper evaluates the feasibility of differentially private federated learning for chest X-ray classification as a defense against data privacy attacks. To the best of our knowledge, we are the first to directly compare the impact of differentially private training on two different neural network architectures, DenseNet121 and ResNet50. Extending the federated learning environments previously analyzed in terms of privacy, we simulated a heterogeneous and imbalanced federated setting by distributing images from the public CheXpert and Mendeley chest X-ray datasets unevenly among 36 clients. Both non-private baseline models achieved an area under the receiver operating characteristic curve (AUC) of 0.940.94 on the binary classification task of detecting the presence of a medical finding. We demonstrate that both model architectures are vulnerable to privacy violation by applying image reconstruction attacks to local model updates from individual clients. The attack was particularly successful during later training stages. To mitigate the risk of a privacy breach, we integrated Rényi differential privacy with a Gaussian noise mechanism into local model training. We evaluate model performance and attack vulnerability for privacy budgets ε∈{1,3,6,10}�∈{1,3,6,10}. The DenseNet121 achieved the best utility-privacy trade-off with an AUC of 0.940.94 for ε=6�=6. Model performance deteriorated slightly for individual clients compared to the non-private baseline. The ResNet50 only reached an AUC of 0.760.76 in the same privacy setting. Its performance was inferior to that of the DenseNet121 for all considered privacy constraints, suggesting that the DenseNet121 architecture is more robust to differentially private training. KW - federated learning KW - privacy and security KW - privacy attack KW - X-ray Y1 - 2022 U6 - https://doi.org/10.3390/s22145195 SN - 1424-8220 VL - 22 PB - MDPI CY - Basel, Schweiz ET - 14 ER - TY - GEN A1 - Ziegler, Joceline A1 - Pfitzner, Bjarne A1 - Schulz, Heinrich A1 - Saalbach, Axel A1 - Arnrich, Bert T1 - Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-ray Data T2 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät N2 - Privacy regulations and the physical distribution of heterogeneous data are often primary concerns for the development of deep learning models in a medical context. This paper evaluates the feasibility of differentially private federated learning for chest X-ray classification as a defense against data privacy attacks. To the best of our knowledge, we are the first to directly compare the impact of differentially private training on two different neural network architectures, DenseNet121 and ResNet50. Extending the federated learning environments previously analyzed in terms of privacy, we simulated a heterogeneous and imbalanced federated setting by distributing images from the public CheXpert and Mendeley chest X-ray datasets unevenly among 36 clients. Both non-private baseline models achieved an area under the receiver operating characteristic curve (AUC) of 0.940.94 on the binary classification task of detecting the presence of a medical finding. We demonstrate that both model architectures are vulnerable to privacy violation by applying image reconstruction attacks to local model updates from individual clients. The attack was particularly successful during later training stages. To mitigate the risk of a privacy breach, we integrated Rényi differential privacy with a Gaussian noise mechanism into local model training. We evaluate model performance and attack vulnerability for privacy budgets ε∈{1,3,6,10}�∈{1,3,6,10}. The DenseNet121 achieved the best utility-privacy trade-off with an AUC of 0.940.94 for ε=6�=6. Model performance deteriorated slightly for individual clients compared to the non-private baseline. The ResNet50 only reached an AUC of 0.760.76 in the same privacy setting. Its performance was inferior to that of the DenseNet121 for all considered privacy constraints, suggesting that the DenseNet121 architecture is more robust to differentially private training. T3 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät - 14 KW - federated learning KW - privacy and security KW - privacy attack KW - X-ray Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-581322 IS - 14 ER - TY - THES A1 - Zieger, Tobias T1 - Self-adaptive data quality BT - automating duplicate detection N2 - Carrying out business processes successfully is closely linked to the quality of the data inventory in an organization. Lacks in data quality lead to problems: Incorrect address data prevents (timely) shipments to customers. Erroneous orders lead to returns and thus to unnecessary effort. Wrong pricing forces companies to miss out on revenues or to impair customer satisfaction. If orders or customer records cannot be retrieved, complaint management takes longer. Due to erroneous inventories, too few or too much supplies might be reordered. A special problem with data quality and the reason for many of the issues mentioned above are duplicates in databases. Duplicates are different representations of same real-world objects in a dataset. However, these representations differ from each other and are for that reason hard to match by a computer. Moreover, the number of required comparisons to find those duplicates grows with the square of the dataset size. To cleanse the data, these duplicates must be detected and removed. Duplicate detection is a very laborious process. To achieve satisfactory results, appropriate software must be created and configured (similarity measures, partitioning keys, thresholds, etc.). Both requires much manual effort and experience. This thesis addresses automation of parameter selection for duplicate detection and presents several novel approaches that eliminate the need for human experience in parts of the duplicate detection process. A pre-processing step is introduced that analyzes the datasets in question and classifies their attributes semantically. Not only do these annotations help understanding the respective datasets, but they also facilitate subsequent steps, for example, by selecting appropriate similarity measures or normalizing the data upfront. This approach works without schema information. Following that, we show a partitioning technique that strongly reduces the number of pair comparisons for the duplicate detection process. The approach automatically finds particularly suitable partitioning keys that simultaneously allow for effective and efficient duplicate retrieval. By means of a user study, we demonstrate that this technique finds partitioning keys that outperform expert suggestions and additionally does not need manual configuration. Furthermore, this approach can be applied independently of the attribute types. To measure the success of a duplicate detection process and to execute the described partitioning approach, a gold standard is required that provides information about the actual duplicates in a training dataset. This thesis presents a technique that uses existing duplicate detection results and crowdsourcing to create a near gold standard that can be used for the purposes above. Another part of the thesis describes and evaluates strategies how to reduce these crowdsourcing costs and to achieve a consensus with less effort. N2 - Die erfolgreiche Ausführung von Geschäftsprozessen ist eng an die Datenqualität der Datenbestände in einer Organisation geknüpft. Bestehen Mängel in der Datenqualität, kann es zu Problemen kommen: Unkorrekte Adressdaten verhindern, dass Kunden (rechtzeitig) beliefert werden. Fehlerhafte Bestellungen führen zu Reklamationen und somit zu unnötigem Aufwand. Falsche Preisauszeichnungen zwingen Unternehmen, auf Einnahmen zu verzichten oder gefährden die Kundenzufriedenheit. Können Bestellungen oder Kundendaten nicht gefunden werden, verlängert sich die Abarbeitung von Beschwerden. Durch fehlerhafte Inventarisierung wird zu wenig oder zu viel Nachschub bestellt. Ein spezielles Datenqualitätsproblem und der Grund für viele der genannten Datenqualitätsprobleme sind Duplikate in Datenbanken. Duplikate sind verschiedene Repräsentationen derselben Realweltobjekte im Datenbestand. Allerdings unterscheiden sich diese Repräsentationen voneinander und sind so für den Computer nur schwer als zusammengehörig zu erkennen. Außerdem wächst die Anzahl der zur Aufdeckung der Duplikate benötigten Vergleiche quadratisch mit der Datensatzgröße. Zum Zwecke der Datenreinigung müssen diese Duplikate erkannt und beseitigt werden. Diese Duplikaterkennung ist ein sehr aufwändiger Prozess. Um gute Ergebnisse zu erzielen, ist die Erstellung von entsprechender Software und das Konfigurieren vieler Parameter (Ähnlichkeitsmaße, Partitionierungsschlüssel, Schwellwerte usw.) nötig. Beides erfordert viel manuellen Aufwand und Erfahrung. Diese Dissertation befasst sich mit dem Automatisieren der Parameterwahl für die Duplikaterkennung und stellt verschiedene neuartige Verfahren vor, durch die Teile des Duplikaterkennungsprozesses ohne menschliche Erfahrung gestaltet werden können. Es wird ein Vorverarbeitungsschritt vorgestellt, der die betreffenden Datensätze analysiert und deren Attribute automatisch semantisch klassifiziert. Durch diese Annotationen wird nicht nur das Verständnis des Datensatzes verbessert, sondern es werden darüber hinaus die folgenden Schritte erleichtert, zum Beispiel können so geeignete Ähnlichkeitsmaße ausgewählt oder die Daten normalisiert werden. Dabei kommt der Ansatz ohne Schemainformationen aus. Anschließend wird ein Partitionierungsverfahren gezeigt, das die Anzahl der für die Duplikaterkennung benötigten Vergleiche stark reduziert. Das Verfahren findet automatisch besonders geeignete Partitionierungsschlüssel, die eine gleichzeitig effektive und effiziente Duplikatsuche ermöglichen. Anhand einer Nutzerstudie wird gezeigt, dass die so gefundenen Partitionierungsschlüssel Expertenvorschlägen überlegen sind und zudem keine menschliche Konfiguration benötigen. Außerdem lässt sich das Verfahren unabhängig von den Attributtypen anwenden. Zum Messen des Erfolges eines Duplikaterkennungsverfahrens und für das zuvor beschriebene Partitionierungsverfahren ist ein Goldstandard nötig, der Auskunft über die zu findenden Duplikate gibt. Die Dissertation stellt ein Verfahren vor, das anhand mehrerer vorhandener Duplikaterkennungsergebnisse und dem Einsatz von Crowdsourcing einen Nahezu-Goldstandard erzeugt, der für die beschriebenen Zwecke eingesetzt werden kann. Ein weiterer Teil der Arbeit beschreibt und evaluiert Strategien, wie die Kosten dieses Crowdsourcingeinsatzes reduziert werden können und mit geringerem Aufwand ein Konsens erreicht wird. KW - data quality KW - Datenqualität KW - Duplikaterkennung KW - duplicate detection KW - Machine Learning KW - Information Retrieval KW - Automatisierung KW - automation Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-410573 ER - TY - JOUR A1 - Zhou, Lin A1 - Fischer, Eric A1 - Tunca, Can A1 - Brahms, Clemens Markus A1 - Ersoy, Cem A1 - Granacher, Urs A1 - Arnrich, Bert T1 - How We Found Our IMU BT - Guidelines to IMU Selection and a Comparison of Seven IMUs for Pervasive Healthcare Applications JF - Sensors N2 - Inertial measurement units (IMUs) are commonly used for localization or movement tracking in pervasive healthcare-related studies, and gait analysis is one of the most often studied topics using IMUs. The increasing variety of commercially available IMU devices offers convenience by combining the sensor modalities and simplifies the data collection procedures. However, selecting the most suitable IMU device for a certain use case is increasingly challenging. In this study, guidelines for IMU selection are proposed. In particular, seven IMUs were compared in terms of their specifications, data collection procedures, and raw data quality. Data collected from the IMUs were then analyzed by a gait analysis algorithm. The difference in accuracy of the calculated gait parameters between the IMUs could be used to retrace the issues in raw data, such as acceleration range or sensor calibration. Based on our algorithm, we were able to identify the best-suited IMUs for our needs. This study provides an overview of how to select the IMUs based on the area of study with concrete examples, and gives insights into the features of seven commercial IMUs using real data. KW - inertial measurement unit KW - pervasive healthcare KW - gait analysis KW - comparison of devices Y1 - 2020 U6 - https://doi.org/10.3390/s20154090 SN - 1424-8220 VL - 20 IS - 15 PB - MDPI CY - Basel ER - TY - GEN A1 - Zhou, Lin A1 - Fischer, Eric A1 - Tunca, Can A1 - Brahms, Clemens Markus A1 - Ersoy, Cem A1 - Granacher, Urs A1 - Arnrich, Bert T1 - How We Found Our IMU BT - Guidelines to IMU Selection and a Comparison of Seven IMUs for Pervasive Healthcare Applications T2 - Postprints der Universität Potsdam : Reihe der Digital Engineering Fakultät N2 - Inertial measurement units (IMUs) are commonly used for localization or movement tracking in pervasive healthcare-related studies, and gait analysis is one of the most often studied topics using IMUs. The increasing variety of commercially available IMU devices offers convenience by combining the sensor modalities and simplifies the data collection procedures. However, selecting the most suitable IMU device for a certain use case is increasingly challenging. In this study, guidelines for IMU selection are proposed. In particular, seven IMUs were compared in terms of their specifications, data collection procedures, and raw data quality. Data collected from the IMUs were then analyzed by a gait analysis algorithm. The difference in accuracy of the calculated gait parameters between the IMUs could be used to retrace the issues in raw data, such as acceleration range or sensor calibration. Based on our algorithm, we were able to identify the best-suited IMUs for our needs. This study provides an overview of how to select the IMUs based on the area of study with concrete examples, and gives insights into the features of seven commercial IMUs using real data. T3 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät - 2 KW - inertial measurement unit KW - pervasive healthcare KW - gait analysis KW - comparison of devices Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-481628 IS - 2 ER - TY - BOOK A1 - Zhang, Shuhao A1 - Plauth, Max A1 - Eberhardt, Felix A1 - Polze, Andreas A1 - Lehmann, Jens A1 - Sejdiu, Gezim A1 - Jabeen, Hajira A1 - Servadei, Lorenzo A1 - Möstl, Christian A1 - Bär, Florian A1 - Netzeband, André A1 - Schmidt, Rainer A1 - Knigge, Marlene A1 - Hecht, Sonja A1 - Prifti, Loina A1 - Krcmar, Helmut A1 - Sapegin, Andrey A1 - Jaeger, David A1 - Cheng, Feng A1 - Meinel, Christoph A1 - Friedrich, Tobias A1 - Rothenberger, Ralf A1 - Sutton, Andrew M. A1 - Sidorova, Julia A. A1 - Lundberg, Lars A1 - Rosander, Oliver A1 - Sköld, Lars A1 - Di Varano, Igor A1 - van der Walt, Estée A1 - Eloff, Jan H. P. A1 - Fabian, Benjamin A1 - Baumann, Annika A1 - Ermakova, Tatiana A1 - Kelkel, Stefan A1 - Choudhary, Yash A1 - Cooray, Thilini A1 - Rodríguez, Jorge A1 - Medina-Pérez, Miguel Angel A1 - Trejo, Luis A. A1 - Barrera-Animas, Ari Yair A1 - Monroy-Borja, Raúl A1 - López-Cuevas, Armando A1 - Ramírez-Márquez, José Emmanuel A1 - Grohmann, Maria A1 - Niederleithinger, Ernst A1 - Podapati, Sasidhar A1 - Schmidt, Christopher A1 - Huegle, Johannes A1 - de Oliveira, Roberto C. L. A1 - Soares, Fábio Mendes A1 - van Hoorn, André A1 - Neumer, Tamas A1 - Willnecker, Felix A1 - Wilhelm, Mathias A1 - Kuster, Bernhard ED - Meinel, Christoph ED - Polze, Andreas ED - Beins, Karsten ED - Strotmann, Rolf ED - Seibold, Ulrich ED - Rödszus, Kurt ED - Müller, Jürgen T1 - HPI Future SOC Lab – Proceedings 2017 T1 - HPI Future SOC Lab – Proceedings 2017 N2 - The “HPI Future SOC Lab” is a cooperation of the Hasso Plattner Institute (HPI) and industry partners. Its mission is to enable and promote exchange and interaction between the research community and the industry partners. The HPI Future SOC Lab provides researchers with free of charge access to a complete infrastructure of state of the art hard and software. This infrastructure includes components, which might be too expensive for an ordinary research environment, such as servers with up to 64 cores and 2 TB main memory. The offerings address researchers particularly from but not limited to the areas of computer science and business information systems. Main areas of research include cloud computing, parallelization, and In-Memory technologies. This technical report presents results of research projects executed in 2017. Selected projects have presented their results on April 25th and November 15th 2017 at the Future SOC Lab Day events. N2 - Das Future SOC Lab am HPI ist eine Kooperation des Hasso-Plattner-Instituts mit verschiedenen Industriepartnern. Seine Aufgabe ist die Ermöglichung und Förderung des Austausches zwischen Forschungsgemeinschaft und Industrie. Am Lab wird interessierten Wissenschaftlern eine Infrastruktur von neuester Hard- und Software kostenfrei für Forschungszwecke zur Verfügung gestellt. Dazu zählen teilweise noch nicht am Markt verfügbare Technologien, die im normalen Hochschulbereich in der Regel nicht zu finanzieren wären, bspw. Server mit bis zu 64 Cores und 2 TB Hauptspeicher. Diese Angebote richten sich insbesondere an Wissenschaftler in den Gebieten Informatik und Wirtschaftsinformatik. Einige der Schwerpunkte sind Cloud Computing, Parallelisierung und In-Memory Technologien. In diesem Technischen Bericht werden die Ergebnisse der Forschungsprojekte des Jahres 2017 vorgestellt. Ausgewählte Projekte stellten ihre Ergebnisse am 25. April und 15. November 2017 im Rahmen der Future SOC Lab Tag Veranstaltungen vor. T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 130 KW - Future SOC Lab KW - research projects KW - multicore architectures KW - In-Memory technology KW - cloud computing KW - machine learning KW - artifical intelligence KW - Future SOC Lab KW - Forschungsprojekte KW - Multicore Architekturen KW - In-Memory Technologie KW - Cloud Computing KW - maschinelles Lernen KW - Künstliche Intelligenz Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-433100 SN - 978-3-86956-475-3 SN - 1613-5652 SN - 2191-1665 IS - 130 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Zenner, Alexander M. A1 - Böttinger, Erwin A1 - Konigorski, Stefan T1 - StudyMe BT - a new mobile app for user-centric N-of-1 trials JF - Trials N2 - N-of-1 trials are multi-crossover self-experiments that allow individuals to systematically evaluate the effect of interventions on their personal health goals. Although several tools for N-of-1 trials exist, there is a gap in supporting non-experts in conducting their own user-centric trials. In this study, we present StudyMe, an open-source mobile application that is freely available from https://play.google.com/store/apps/details?id=health.studyu.me and offers users flexibility and guidance in configuring every component of their trials. We also present research that informed the development of StudyMe, focusing on trial creation. Through an initial survey with 272 participants, we learned that individuals are interested in a variety of personal health aspects and have unique ideas on how to improve them. In an iterative, user-centered development process with intermediate user tests, we developed StudyMe that features an educational part to communicate N-of-1 trial concepts. A final empirical evaluation of StudyMe showed that all participants were able to create their own trials successfully using StudyMe and the app achieved a very good usability rating. Our findings suggest that StudyMe provides a significant step towards enabling individuals to apply a systematic science-oriented approach to personalize health-related interventions and behavior modifications in their everyday lives. Y1 - 2022 U6 - https://doi.org/10.1186/s13063-022-06893-7 SN - 1745-6215 VL - 23 PB - BioMed Central CY - London ER - TY - GEN A1 - Zenner, Alexander M. A1 - Böttinger, Erwin A1 - Konigorski, Stefan T1 - StudyMe BT - a new mobile app for user-centric N-of-1 trials T2 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät N2 - N-of-1 trials are multi-crossover self-experiments that allow individuals to systematically evaluate the effect of interventions on their personal health goals. Although several tools for N-of-1 trials exist, there is a gap in supporting non-experts in conducting their own user-centric trials. In this study, we present StudyMe, an open-source mobile application that is freely available from https://play.google.com/store/apps/details?id=health.studyu.me and offers users flexibility and guidance in configuring every component of their trials. We also present research that informed the development of StudyMe, focusing on trial creation. Through an initial survey with 272 participants, we learned that individuals are interested in a variety of personal health aspects and have unique ideas on how to improve them. In an iterative, user-centered development process with intermediate user tests, we developed StudyMe that features an educational part to communicate N-of-1 trial concepts. A final empirical evaluation of StudyMe showed that all participants were able to create their own trials successfully using StudyMe and the app achieved a very good usability rating. Our findings suggest that StudyMe provides a significant step towards enabling individuals to apply a systematic science-oriented approach to personalize health-related interventions and behavior modifications in their everyday lives. T3 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät - 18 Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-589763 IS - 18 ER - TY - JOUR A1 - Yousfi, Alaaeddine A1 - Hewelt, Marcin A1 - Bauer, Christine A1 - Weske, Mathias T1 - Toward uBPMN-Based patterns for modeling ubiquitous business processes JF - IEEE Transactions on Industrial Informatics N2 - Ubiquitous business processes are the new generation of processes that pervade the physical space and interact with their environments using a minimum of human involvement. Although they are now widely deployed in the industry, their deployment is still ad hoc . They are implemented after an arbitrary modeling phase or no modeling phase at all. The absence of a solid modeling phase backing up the implementation generates many loopholes that are stressed in the literature. Here, we tackle the issue of modeling ubiquitous business processes. We propose patterns to represent the recent ubiquitous computing features. These patterns are the outcome of an analysis we conducted in the field of human-computer interaction to examine how the features are actually deployed. The patterns' understandability, ease-of-use, usefulness, and completeness are examined via a user experiment. The results indicate that these four indexes are on the positive track. Hence, the patterns may be the backbone of ubiquitous business process modeling in industrial applications. KW - Ubiquitous business process KW - ubiquitous business process model and notation (uBPMN) KW - ubiquitous business process modeling KW - ubiquitous computing (ubicomp) Y1 - 2017 U6 - https://doi.org/10.1109/TII.2017.2777847 SN - 1551-3203 SN - 1941-0050 VL - 14 IS - 8 SP - 3358 EP - 3367 PB - Inst. of Electr. and Electronics Engineers CY - Piscataway ER - TY - JOUR A1 - Yousfi, Alaaeddine A1 - Batoulis, Kimon A1 - Weske, Mathias T1 - Achieving Business Process Improvement via Ubiquitous Decision-Aware Business Processes JF - ACM Transactions on Internet Technology N2 - Business process improvement is an endless challenge for many organizations. As long as there is a process, it must he improved. Nowadays, improvement initiatives are driven by professionals. This is no longer practical because people cannot perceive the enormous data of current business environments. Here, we introduce ubiquitous decision-aware business processes. They pervade the physical space, analyze the ever-changing environments, and make decisions accordingly. We explain how they can be built and used for improvement. Our approach can be a valuable improvement option to alleviate the workload of participants by helping focus on the crucial rather than the menial tasks. KW - Business process improvement KW - ubiquitous decision-aware business process KW - ubiquitous decisions KW - context KW - uBPMN KW - DMN Y1 - 2019 U6 - https://doi.org/10.1145/3298986 SN - 1533-5399 SN - 1557-6051 VL - 19 IS - 1 PB - Association for Computing Machinery CY - New York ER - TY - THES A1 - Yang, Haojin T1 - Deep representation learning for multimedia data analysis Y1 - 2019 ER - TY - JOUR A1 - Xue, Wei A1 - Bruillard, Éric ED - Meinel, Christoph ED - Schweiger, Stefanie ED - Staubitz, Thomas ED - Conrad, Robert ED - Alario Hoyos, Carlos ED - Ebner, Martin ED - Sancassani, Susanna ED - Żur, Agnieszka ED - Friedl, Christian ED - Halawa, Sherif ED - Gamage, Dilrukshi ED - Scott, Jeffrey ED - Kristine Jonson Carlon, May ED - Deville, Yves ED - Gaebel, Michael ED - Delgado Kloos, Carlos ED - von Schmieden, Karen T1 - MOOC in private Chinese universities BT - behavior and attitude of students learning foreign languages JF - EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash? N2 - This paper investigates private university students’ language learning activities in MOOC platforms and their attitude toward it. The study explores the development of MOOC use in Chinese private universities, with a focus on two modes: online et blended. We conducted empirical studies with students learning French and Japanese as a second foreign language, using questionnaires (N = 387) and interviews (N = 20) at a private university in Wuhan. Our results revealed that the majority of students used the MOOC platform more than twice a week and focused on the MOOC video, materials and assignments. However, we also found that students showed less interest in online communication (forums). Those who worked in the blended learning mode, especially Japanese learning students, had a more positive attitude toward MOOCs than other students. KW - Digitale Bildung KW - Kursdesign KW - MOOC KW - Micro Degree KW - Online-Lehre KW - Onlinekurs KW - Onlinekurs-Produktion KW - digital education KW - e-learning KW - micro degree KW - micro-credential KW - online course creation KW - online course design KW - online teaching Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-621811 SP - 37 EP - 45 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Xiaoxiao, Wang A1 - Shuangshuang, Guo ED - Meinel, Christoph ED - Schweiger, Stefanie ED - Staubitz, Thomas ED - Conrad, Robert ED - Alario Hoyos, Carlos ED - Ebner, Martin ED - Sancassani, Susanna ED - Żur, Agnieszka ED - Friedl, Christian ED - Halawa, Sherif ED - Gamage, Dilrukshi ED - Scott, Jeffrey ED - Kristine Jonson Carlon, May ED - Deville, Yves ED - Gaebel, Michael ED - Delgado Kloos, Carlos ED - von Schmieden, Karen T1 - Promoting global higher education cooperation BT - taking global MOOC and online education alliance as an example JF - EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash? N2 - The massive growth of MOOCs in 2011 laid the groundwork for the achievement of SDG 4. With the various benefits of MOOCs, there is also anticipation that online education should focus on more interactivity and global collaboration. In this context, the Global MOOC and Online Education Alliance (GMA) established a diverse group of 17 world-leading universities and three online education platforms from across 14 countries on all six continents in 2020. Through nearly three years of exploration, GMA has gained experience and achieved progress in fostering global cooperation in higher education. First, in joint teaching, GMA has promoted in-depth cooperation between members inside and outside the alliance. Examples include promoting the exchange of high-quality MOOCs, encouraging the creation of Global Hybrid Classroom, and launching Global Hybrid Classroom Certificate Programs. Second, in capacity building and knowledge sharing, GMA has launched Online Education Dialogues and the Global MOOC and Online Education Conference, inviting global experts to share best practices and attracting more than 10 million viewers around the world. Moreover, GMA is collaborating with international organizations to support teachers’ professional growth, create an online learning community, and serve as a resource for further development. Third, in public advocacy, GMA has launched the SDG Hackathon and Global Massive Open Online Challenge (GMOOC) and attracted global learners to acquire knowledge and incubate their innovative ideas within a cross-cultural community to solve real-world problems that all humans face and jointly create a better future. Based on past experiences and challenges, GMA will explore more diverse cooperation models with more partners utilizing advanced technology, provide more support for digital transformation in higher education, and further promote global cooperation towards building a human community with a shared future. KW - Digitale Bildung KW - Kursdesign KW - MOOC KW - Micro Degree KW - Online-Lehre KW - Onlinekurs KW - Onlinekurs-Produktion KW - digital education KW - e-learning KW - micro degree KW - micro-credential KW - online course creation KW - online course design KW - online teaching Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-623865 SP - 85 EP - 93 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Wuttke, Matthias A1 - Li, Yong A1 - Li, Man A1 - Sieber, Karsten B. A1 - Feitosa, Mary F. A1 - Gorski, Mathias A1 - Tin, Adrienne A1 - Wang, Lihua A1 - Chu, Audrey Y. A1 - Hoppmann, Anselm A1 - Kirsten, Holger A1 - Giri, Ayush A1 - Chai, Jin-Fang A1 - Sveinbjornsson, Gardar A1 - Tayo, Bamidele O. A1 - Nutile, Teresa A1 - Fuchsberger, Christian A1 - Marten, Jonathan A1 - Cocca, Massimiliano A1 - Ghasemi, Sahar A1 - Xu, Yizhe A1 - Horn, Katrin A1 - Noce, Damia A1 - Van der Most, Peter J. A1 - Sedaghat, Sanaz A1 - Yu, Zhi A1 - Akiyama, Masato A1 - Afaq, Saima A1 - Ahluwalia, Tarunveer Singh A1 - Almgren, Peter A1 - Amin, Najaf A1 - Arnlov, Johan A1 - Bakker, Stephan J. L. A1 - Bansal, Nisha A1 - Baptista, Daniela A1 - Bergmann, Sven A1 - Biggs, Mary L. A1 - Biino, Ginevra A1 - Boehnke, Michael A1 - Boerwinkle, Eric A1 - Boissel, Mathilde A1 - Böttinger, Erwin A1 - Boutin, Thibaud S. A1 - Brenner, Hermann A1 - Brumat, Marco A1 - Burkhardt, Ralph A1 - Butterworth, Adam S. A1 - Campana, Eric A1 - Campbell, Archie A1 - Campbell, Harry A1 - Canouil, Mickael A1 - Carroll, Robert J. A1 - Catamo, Eulalia A1 - Chambers, John C. A1 - Chee, Miao-Ling A1 - Chee, Miao-Li A1 - Chen, Xu A1 - Cheng, Ching-Yu A1 - Cheng, Yurong A1 - Christensen, Kaare A1 - Cifkova, Renata A1 - Ciullo, Marina A1 - Concas, Maria Pina A1 - Cook, James P. A1 - Coresh, Josef A1 - Corre, Tanguy A1 - Sala, Cinzia Felicita A1 - Cusi, Daniele A1 - Danesh, John A1 - Daw, E. Warwick A1 - De Borst, Martin H. A1 - De Grandi, Alessandro A1 - De Mutsert, Renee A1 - De Vries, Aiko P. J. A1 - Degenhardt, Frauke A1 - Delgado, Graciela A1 - Demirkan, Ayse A1 - Di Angelantonio, Emanuele A1 - Dittrich, Katalin A1 - Divers, Jasmin A1 - Dorajoo, Rajkumar A1 - Eckardt, Kai-Uwe A1 - Ehret, Georg A1 - Elliott, Paul A1 - Endlich, Karlhans A1 - Evans, Michele K. A1 - Felix, Janine F. A1 - Foo, Valencia Hui Xian A1 - Franco, Oscar H. A1 - Franke, Andre A1 - Freedman, Barry I. A1 - Freitag-Wolf, Sandra A1 - Friedlander, Yechiel A1 - Froguel, Philippe A1 - Gansevoort, Ron T. A1 - Gao, He A1 - Gasparini, Paolo A1 - Gaziano, J. Michael A1 - Giedraitis, Vilmantas A1 - Gieger, Christian A1 - Girotto, Giorgia A1 - Giulianini, Franco A1 - Gogele, Martin A1 - Gordon, Scott D. A1 - Gudbjartsson, Daniel F. A1 - Gudnason, Vilmundur A1 - Haller, Toomas A1 - Hamet, Pavel A1 - Harris, Tamara B. A1 - Hartman, Catharina A. A1 - Hayward, Caroline A1 - Hellwege, Jacklyn N. A1 - Heng, Chew-Kiat A1 - Hicks, Andrew A. A1 - Hofer, Edith A1 - Huang, Wei A1 - Hutri-Kahonen, Nina A1 - Hwang, Shih-Jen A1 - Ikram, M. Arfan A1 - Indridason, Olafur S. A1 - Ingelsson, Erik A1 - Ising, Marcus A1 - Jaddoe, Vincent W. V. A1 - Jakobsdottir, Johanna A1 - Jonas, Jost B. A1 - Joshi, Peter K. A1 - Josyula, Navya Shilpa A1 - Jung, Bettina A1 - Kahonen, Mika A1 - Kamatani, Yoichiro A1 - Kammerer, Candace M. A1 - Kanai, Masahiro A1 - Kastarinen, Mika A1 - Kerr, Shona M. A1 - Khor, Chiea-Chuen A1 - Kiess, Wieland A1 - Kleber, Marcus E. A1 - Koenig, Wolfgang A1 - Kooner, Jaspal S. A1 - Korner, Antje A1 - Kovacs, Peter A1 - Kraja, Aldi T. A1 - Krajcoviechova, Alena A1 - Kramer, Holly A1 - Kramer, Bernhard K. A1 - Kronenberg, Florian A1 - Kubo, Michiaki A1 - Kuhnel, Brigitte A1 - Kuokkanen, Mikko A1 - Kuusisto, Johanna A1 - La Bianca, Martina A1 - Laakso, Markku A1 - Lange, Leslie A. A1 - Langefeld, Carl D. A1 - Lee, Jeannette Jen-Mai A1 - Lehne, Benjamin A1 - Lehtimaki, Terho A1 - Lieb, Wolfgang A1 - Lim, Su-Chi A1 - Lind, Lars A1 - Lindgren, Cecilia M. A1 - Liu, Jun A1 - Liu, Jianjun A1 - Loeffler, Markus A1 - Loos, Ruth J. F. A1 - Lucae, Susanne A1 - Lukas, Mary Ann A1 - Lyytikainen, Leo-Pekka A1 - Magi, Reedik A1 - Magnusson, Patrik K. E. A1 - Mahajan, Anubha A1 - Martin, Nicholas G. A1 - Martins, Jade A1 - Marz, Winfried A1 - Mascalzoni, Deborah A1 - Matsuda, Koichi A1 - Meisinger, Christa A1 - Meitinger, Thomas A1 - Melander, Olle A1 - Metspalu, Andres A1 - Mikaelsdottir, Evgenia K. A1 - Milaneschi, Yuri A1 - Miliku, Kozeta A1 - Mishra, Pashupati P. A1 - Program, V. A. Million Veteran A1 - Mohlke, Karen L. A1 - Mononen, Nina A1 - Montgomery, Grant W. A1 - Mook-Kanamori, Dennis O. A1 - Mychaleckyj, Josyf C. A1 - Nadkarni, Girish N. A1 - Nalls, Mike A. A1 - Nauck, Matthias A1 - Nikus, Kjell A1 - Ning, Boting A1 - Nolte, Ilja M. A1 - Noordam, Raymond A1 - Olafsson, Isleifur A1 - Oldehinkel, Albertine J. A1 - Orho-Melander, Marju A1 - Ouwehand, Willem H. A1 - Padmanabhan, Sandosh A1 - Palmer, Nicholette D. A1 - Palsson, Runolfur A1 - Penninx, Brenda W. J. H. A1 - Perls, Thomas A1 - Perola, Markus A1 - Pirastu, Mario A1 - Pirastu, Nicola A1 - Pistis, Giorgio A1 - Podgornaia, Anna I. A1 - Polasek, Ozren A1 - Ponte, Belen A1 - Porteous, David J. A1 - Poulain, Tanja A1 - Pramstaller, Peter P. A1 - Preuss, Michael H. A1 - Prins, Bram P. A1 - Province, Michael A. A1 - Rabelink, Ton J. A1 - Raffield, Laura M. A1 - Raitakari, Olli T. A1 - Reilly, Dermot F. A1 - Rettig, Rainer A1 - Rheinberger, Myriam A1 - Rice, Kenneth M. A1 - Ridker, Paul M. A1 - Rivadeneira, Fernando A1 - Rizzi, Federica A1 - Roberts, David J. A1 - Robino, Antonietta A1 - Rossing, Peter A1 - Rudan, Igor A1 - Rueedi, Rico A1 - Ruggiero, Daniela A1 - Ryan, Kathleen A. A1 - Saba, Yasaman A1 - Sabanayagam, Charumathi A1 - Salomaa, Veikko A1 - Salvi, Erika A1 - Saum, Kai-Uwe A1 - Schmidt, Helena A1 - Schmidt, Reinhold A1 - Ben Schottker, A1 - Schulz, Christina-Alexandra A1 - Schupf, Nicole A1 - Shaffer, Christian M. A1 - Shi, Yuan A1 - Smith, Albert V. A1 - Smith, Blair H. A1 - Soranzo, Nicole A1 - Spracklen, Cassandra N. A1 - Strauch, Konstantin A1 - Stringham, Heather M. A1 - Stumvoll, Michael A1 - Svensson, Per O. A1 - Szymczak, Silke A1 - Tai, E-Shyong A1 - Tajuddin, Salman M. A1 - Tan, Nicholas Y. Q. A1 - Taylor, Kent D. A1 - Teren, Andrej A1 - Tham, Yih-Chung A1 - Thiery, Joachim A1 - Thio, Chris H. L. A1 - Thomsen, Hauke A1 - Thorleifsson, Gudmar A1 - Toniolo, Daniela A1 - Tonjes, Anke A1 - Tremblay, Johanne A1 - Tzoulaki, Ioanna A1 - Uitterlinden, Andre G. A1 - Vaccargiu, Simona A1 - Van Dam, Rob M. A1 - Van der Harst, Pim A1 - Van Duijn, Cornelia M. A1 - Edward, Digna R. Velez A1 - Verweij, Niek A1 - Vogelezang, Suzanne A1 - Volker, Uwe A1 - Vollenweider, Peter A1 - Waeber, Gerard A1 - Waldenberger, Melanie A1 - Wallentin, Lars A1 - Wang, Ya Xing A1 - Wang, Chaolong A1 - Waterworth, Dawn M. A1 - Bin Wei, Wen A1 - White, Harvey A1 - Whitfield, John B. A1 - Wild, Sarah H. A1 - Wilson, James F. A1 - Wojczynski, Mary K. A1 - Wong, Charlene A1 - Wong, Tien-Yin A1 - Xu, Liang A1 - Yang, Qiong A1 - Yasuda, Masayuki A1 - Yerges-Armstrong, Laura M. A1 - Zhang, Weihua A1 - Zonderman, Alan B. A1 - Rotter, Jerome I. A1 - Bochud, Murielle A1 - Psaty, Bruce M. A1 - Vitart, Veronique A1 - Wilson, James G. A1 - Dehghan, Abbas A1 - Parsa, Afshin A1 - Chasman, Daniel I. A1 - Ho, Kevin A1 - Morris, Andrew P. A1 - Devuyst, Olivier A1 - Akilesh, Shreeram A1 - Pendergrass, Sarah A. A1 - Sim, Xueling A1 - Boger, Carsten A. A1 - Okada, Yukinori A1 - Edwards, Todd L. A1 - Snieder, Harold A1 - Stefansson, Kari A1 - Hung, Adriana M. A1 - Heid, Iris M. A1 - Scholz, Markus A1 - Teumer, Alexander A1 - Kottgen, Anna A1 - Pattaro, Cristian T1 - A catalog of genetic loci associated with kidney function from analyses of a million individuals JF - Nature genetics N2 - Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through transancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n = 1,046,070), we identified 264 associated loci (166 new). Of these,147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research. Y1 - 2019 U6 - https://doi.org/10.1038/s41588-019-0407-x SN - 1061-4036 SN - 1546-1718 VL - 51 IS - 6 SP - 957 EP - + PB - Nature Publ. Group CY - New York ER - TY - THES A1 - Wolf, Johannes T1 - Analysis and visualization of transport infrastructure based on large-scale geospatial mobile mapping data T1 - Analyse und Visualisierung von Verkehrsinfrastruktur basierend auf großen Mobile-Mapping-Datensätzen N2 - 3D point clouds are a universal and discrete digital representation of three-dimensional objects and environments. For geospatial applications, 3D point clouds have become a fundamental type of raw data acquired and generated using various methods and techniques. In particular, 3D point clouds serve as raw data for creating digital twins of the built environment. This thesis concentrates on the research and development of concepts, methods, and techniques for preprocessing, semantically enriching, analyzing, and visualizing 3D point clouds for applications around transport infrastructure. It introduces a collection of preprocessing techniques that aim to harmonize raw 3D point cloud data, such as point density reduction and scan profile detection. Metrics such as, e.g., local density, verticality, and planarity are calculated for later use. One of the key contributions tackles the problem of analyzing and deriving semantic information in 3D point clouds. Three different approaches are investigated: a geometric analysis, a machine learning approach operating on synthetically generated 2D images, and a machine learning approach operating on 3D point clouds without intermediate representation. In the first application case, 2D image classification is applied and evaluated for mobile mapping data focusing on road networks to derive road marking vector data. The second application case investigates how 3D point clouds can be merged with ground-penetrating radar data for a combined visualization and to automatically identify atypical areas in the data. For example, the approach detects pavement regions with developing potholes. The third application case explores the combination of a 3D environment based on 3D point clouds with panoramic imagery to improve visual representation and the detection of 3D objects such as traffic signs. The presented methods were implemented and tested based on software frameworks for 3D point clouds and 3D visualization. In particular, modules for metric computation, classification procedures, and visualization techniques were integrated into a modular pipeline-based C++ research framework for geospatial data processing, extended by Python machine learning scripts. All visualization and analysis techniques scale to large real-world datasets such as road networks of entire cities or railroad networks. The thesis shows that some use cases allow taking advantage of established image vision methods to analyze images rendered from mobile mapping data efficiently. The two presented semantic classification methods working directly on 3D point clouds are use case independent and show similar overall accuracy when compared to each other. While the geometry-based method requires less computation time, the machine learning-based method supports arbitrary semantic classes but requires training the network with ground truth data. Both methods can be used in combination to gradually build this ground truth with manual corrections via a respective annotation tool. This thesis contributes results for IT system engineering of applications, systems, and services that require spatial digital twins of transport infrastructure such as road networks and railroad networks based on 3D point clouds as raw data. It demonstrates the feasibility of fully automated data flows that map captured 3D point clouds to semantically classified models. This provides a key component for seamlessly integrated spatial digital twins in IT solutions that require up-to-date, object-based, and semantically enriched information about the built environment. N2 - 3D-Punktwolken sind eine universelle und diskrete digitale Darstellung von dreidimensionalen Objekten und Umgebungen. Für raumbezogene Anwendungen sind 3D-Punktwolken zu einer grundlegenden Form von Rohdaten geworden, die mit verschiedenen Methoden und Techniken erfasst und erzeugt werden. Insbesondere dienen 3D-Punktwolken als Rohdaten für die Erstellung digitaler Zwillinge der bebauten Umwelt. Diese Arbeit konzentriert sich auf die Erforschung und Entwicklung von Konzepten, Methoden und Techniken zur Vorverarbeitung, semantischen Anreicherung, Analyse und Visualisierung von 3D-Punktwolken für Anwendungen im Bereich der Verkehrsinfrastruktur. Es wird eine Sammlung von Vorverarbeitungstechniken vorgestellt, die auf die Harmonisierung von 3D-Punktwolken-Rohdaten abzielen, so z.B. die Reduzierung der Punktdichte und die Erkennung von Scanprofilen. Metriken wie bspw. die lokale Dichte, Vertikalität und Planarität werden zur späteren Verwendung berechnet. Einer der Hauptbeiträge befasst sich mit dem Problem der Analyse und Ableitung semantischer Informationen in 3D-Punktwolken. Es werden drei verschiedene Ansätze untersucht: Eine geometrische Analyse sowie zwei maschinelle Lernansätze, die auf synthetisch erzeugten 2D-Bildern, bzw. auf 3D-Punktwolken ohne Zwischenrepräsentation arbeiten. Im ersten Anwendungsfall wird die 2D-Bildklassifikation für Mobile-Mapping-Daten mit Fokus auf Straßennetze angewendet und evaluiert, um Vektordaten für Straßenmarkierungen abzuleiten. Im zweiten Anwendungsfall wird untersucht, wie 3D-Punktwolken mit Bodenradardaten für eine kombinierte Visualisierung und automatische Identifikation atypischer Bereiche in den Daten zusammengeführt werden können. Der Ansatz erkennt zum Beispiel Fahrbahnbereiche mit entstehenden Schlaglöchern. Der dritte Anwendungsfall untersucht die Kombination einer 3D-Umgebung auf Basis von 3D-Punktwolken mit Panoramabildern, um die visuelle Darstellung und die Erkennung von 3D-Objekten wie Verkehrszeichen zu verbessern. Die vorgestellten Methoden wurden auf Basis von Software-Frameworks für 3D-Punktwolken und 3D-Visualisierung implementiert und getestet. Insbesondere wurden Module für Metrikberechnungen, Klassifikationsverfahren und Visualisierungstechniken in ein modulares, pipelinebasiertes C++-Forschungsframework für die Geodatenverarbeitung integriert, das durch Python-Skripte für maschinelles Lernen erweitert wurde. Alle Visualisierungs- und Analysetechniken skalieren auf große reale Datensätze wie Straßennetze ganzer Städte oder Eisenbahnnetze. Die Arbeit zeigt, dass es in einigen Anwendungsfällen möglich ist, die Vorteile etablierter Bildverarbeitungsmethoden zu nutzen, um aus Mobile-Mapping-Daten gerenderte Bilder effizient zu analysieren. Die beiden vorgestellten semantischen Klassifikationsverfahren, die direkt auf 3D-Punktwolken arbeiten, sind anwendungsfallunabhängig und zeigen im Vergleich zueinander eine ähnliche Gesamtgenauigkeit. Während die geometriebasierte Methode weniger Rechenzeit benötigt, unterstützt die auf maschinellem Lernen basierende Methode beliebige semantische Klassen, erfordert aber das Trainieren des Netzwerks mit Ground-Truth-Daten. Beide Methoden können in Kombination verwendet werden, um diese Ground Truth mit manuellen Korrekturen über ein entsprechendes Annotationstool schrittweise aufzubauen. Diese Arbeit liefert Ergebnisse für das IT-System-Engineering von Anwendungen, Systemen und Diensten, die räumliche digitale Zwillinge von Verkehrsinfrastruktur wie Straßen- und Schienennetzen auf der Basis von 3D-Punktwolken als Rohdaten benötigen. Sie demonstriert die Machbarkeit von vollautomatisierten Datenflüssen, die erfasste 3D-Punktwolken auf semantisch klassifizierte Modelle abbilden. Dies stellt eine Schlüsselkomponente für nahtlos integrierte räumliche digitale Zwillinge in IT-Lösungen dar, die aktuelle, objektbasierte und semantisch angereicherte Informationen über die bebaute Umwelt benötigen. KW - 3D point cloud KW - geospatial data KW - mobile mapping KW - semantic classification KW - 3D visualization KW - 3D-Punktwolke KW - räumliche Geodaten KW - Mobile Mapping KW - semantische Klassifizierung KW - 3D-Visualisierung Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-536129 ER - TY - JOUR A1 - Wittig, Alice A1 - Miranda, Fabio Malcher A1 - Hölzer, Martin A1 - Altenburg, Tom A1 - Bartoszewicz, Jakub Maciej A1 - Beyvers, Sebastian A1 - Dieckmann, Marius Alfred A1 - Genske, Ulrich A1 - Giese, Sven Hans-Joachim A1 - Nowicka, Melania A1 - Richard, Hugues A1 - Schiebenhoefer, Henning A1 - Schmachtenberg, Anna-Juliane A1 - Sieben, Paul A1 - Tang, Ming A1 - Tembrockhaus, Julius A1 - Renard, Bernhard Y. A1 - Fuchs, Stephan T1 - CovRadar BT - continuously tracking and filtering SARS-CoV-2 mutations for genomic surveillance JF - Bioinformatics N2 - The ongoing pandemic caused by SARS-CoV-2 emphasizes the importance of genomic surveillance to understand the evolution of the virus, to monitor the viral population, and plan epidemiological responses. Detailed analysis, easy visualization and intuitive filtering of the latest viral sequences are powerful for this purpose. We present CovRadar, a tool for genomic surveillance of the SARS-CoV-2 Spike protein. CovRadar consists of an analytical pipeline and a web application that enable the analysis and visualization of hundreds of thousand sequences. First, CovRadar extracts the regions of interest using local alignment, then builds a multiple sequence alignment, infers variants and consensus and finally presents the results in an interactive app, making accessing and reporting simple, flexible and fast. Y1 - 2022 U6 - https://doi.org/10.1093/bioinformatics/btac411 SN - 1367-4803 SN - 1367-4811 VL - 38 IS - 17 SP - 4223 EP - 4225 PB - Oxford Univ. Press CY - Oxford ER - TY - GEN A1 - Welearegai, Gebrehiwet B. A1 - Schlueter, Max A1 - Hammer, Christian T1 - Static security evaluation of an industrial web application T2 - Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing N2 - JavaScript is the most popular programming language for web applications. Static analysis of JavaScript applications is highly challenging due to its dynamic language constructs and event-driven asynchronous executions, which also give rise to many security-related bugs. Several static analysis tools to detect such bugs exist, however, research has not yet reported much on the precision and scalability trade-off of these analyzers. As a further obstacle, JavaScript programs structured in Node. js modules need to be collected for analysis, but existing bundlers are either specific to their respective analysis tools or not particularly suitable for static analysis. KW - JavaScript KW - WALA KW - SAFE KW - comparison Y1 - 2019 SN - 978-1-4503-5933-7 U6 - https://doi.org/10.1145/3297280.3297471 SP - 1952 EP - 1961 PB - Association for Computing Machinery CY - New York ER - TY - BOOK A1 - Weber, Benedikt T1 - Human pose estimation for decubitus prophylaxis T1 - Verwendung von Posenabschätzung zur Dekubitusprophylaxe N2 - Decubitus is one of the most relevant diseases in nursing and the most expensive to treat. It is caused by sustained pressure on tissue, so it particularly affects bed-bound patients. This work lays a foundation for pressure mattress-based decubitus prophylaxis by implementing a solution to the single-frame 2D Human Pose Estimation problem. For this, methods of Deep Learning are employed. Two approaches are examined, a coarse-to-fine Convolutional Neural Network for direct regression of joint coordinates and a U-Net for the derivation of probability distribution heatmaps. We conclude that training our models on a combined dataset of the publicly available Bodies at Rest and SLP data yields the best results. Furthermore, various preprocessing techniques are investigated, and a hyperparameter optimization is performed to discover an improved model architecture. Another finding indicates that the heatmap-based approach outperforms direct regression. This model achieves a mean per-joint position error of 9.11 cm for the Bodies at Rest data and 7.43 cm for the SLP data. We find that it generalizes well on data from mattresses other than those seen during training but has difficulties detecting the arms correctly. Additionally, we give a brief overview of the medical data annotation tool annoto we developed in the bachelor project and furthermore conclude that the Scrum framework and agile practices enhanced our development workflow. N2 - Dekubitus ist eine der relevantesten Krankheiten in der Krankenpflege und die kostspieligste in der Behandlung. Sie wird durch anhaltenden Druck auf Gewebe verursacht, betrifft also insbesondere bettlägerige Patienten. Diese Arbeit legt eine Grundlage für druckmatratzenbasierte Dekubitusprophylaxe, indem eine Lösung für das Einzelbild-2D-Posenabschätzungsproblem implementiert wird. Dafür werden Methoden des tiefen Lernens verwendet. Zwei Ansätze, basierend auf einem Gefalteten Neuronalen grob-zu-fein Netzwerk zur direkten Regression der Gelenkkoordinaten und auf einem U-Netzwerk zur Ableitung von Wahrscheinlichkeitsverteilungsbildern, werden untersucht. Wir schlussfolgern, dass das Training unserer Modelle auf einem kombinierten Datensatz, bestehend aus den frei verfügbaren Bodies at Rest und SLP Daten, die besten Ergebnisse liefert. Weiterhin werden diverse Vorverarbeitungsverfahren untersucht und eine Hyperparameteroptimierung zum Finden einer verbesserten Modellarchitektur durchgeführt. Der wahrscheinlichkeitsverteilungsbasierte Ansatz übertrifft die direkte Regression. Dieses Modell erreicht einen durchschnittlichen Pro-Gelenk-Positionsfehler von 9,11 cm auf den Bodies at Rest und von 7,43 cm auf den SLP Daten. Wir sehen, dass es gut auf Daten anderer als der im Training verwendeten Matratzen funktioniert, aber Schwierigkeiten mit der korrekten Erkennung der Arme hat. Weiterhin geben wir eine kurze Übersicht des medizinischen Datenannotationstools annoto, welches wir im Zusammenhang mit dem Bachelorprojekt entwickelt haben, und schlussfolgern außerdem, dass Scrum und agile Praktiken unseren Entwicklungsprozess verbessert haben. T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 153 KW - machine learning KW - deep learning KW - convolutional neural networks KW - pose estimation KW - decubitus KW - telemedicine KW - maschinelles Lernen KW - tiefes Lernen KW - gefaltete neuronale Netze KW - Posenabschätzung KW - Dekubitus KW - Telemedizin Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-567196 SN - 978-3-86956-551-4 SN - 1613-5652 SN - 2191-1665 IS - 153 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Wasilewski, Julie A1 - Khaneboubi, Mehdi A1 - Bruillard, Éric ED - Meinel, Christoph ED - Schweiger, Stefanie ED - Staubitz, Thomas ED - Conrad, Robert ED - Alario Hoyos, Carlos ED - Ebner, Martin ED - Sancassani, Susanna ED - Żur, Agnieszka ED - Friedl, Christian ED - Halawa, Sherif ED - Gamage, Dilrukshi ED - Scott, Jeffrey ED - Kristine Jonson Carlon, May ED - Deville, Yves ED - Gaebel, Michael ED - Delgado Kloos, Carlos ED - von Schmieden, Karen T1 - How to detect At-Risk learners in professional finance MOOCs BT - step one JF - EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash? N2 - “Financial Analysis” is an online course designed for professionals consisting of three MOOCs, offering a professionally and institutionally recognized certificate in finance. The course is open but not free of charge and attracts mostly professionals from the banking industry. The primary objective of this study is to identify indicators that can predict learners at high risk of failure. To achieve this, we analyzed data from a previous course that had 875 enrolled learners and involve in the course during Fall 2021. We utilized correspondence analysis to examine demographic and behavioral variables. The initial results indicate that demographic factors have a minor impact on the risk of failure in comparison to learners’ behaviors on the course platform. Two primary profiles were identified: (1) successful learners who utilized all the documents offered and spent between one to two hours per week, and (2) unsuccessful learners who used less than half of the proposed documents and spent less than one hour per week. Between these groups, at-risk students were identified as those who used more than half of the proposed documents and spent more than two hours per week. The goal is to identify those in group 1 who may be at risk of failing and those in group 2 who may succeed in the current MOOC, and to implement strategies to assist all learners in achieving success. KW - Digitale Bildung KW - Kursdesign KW - MOOC KW - Micro Degree KW - Online-Lehre KW - Onlinekurs KW - Onlinekurs-Produktion KW - digital education KW - e-learning KW - micro degree KW - micro-credential KW - online course creation KW - online course design KW - online teaching Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-624818 SP - 305 EP - 316 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Vollmer, Jan Ole A1 - Trapp, Matthias A1 - Schumann, Heidrun A1 - Döllner, Jürgen Roland Friedrich T1 - Hierarchical spatial aggregation for level-of-detail visualization of 3D thematic data JF - ACM transactions on spatial algorithms and systems N2 - Thematic maps are a common tool to visualize semantic data with a spatial reference. Combining thematic data with a geometric representation of their natural reference frame aids the viewer’s ability in gaining an overview, as well as perceiving patterns with respect to location; however, as the amount of data for visualization continues to increase, problems such as information overload and visual clutter impede perception, requiring data aggregation and level-of-detail visualization techniques. While existing aggregation techniques for thematic data operate in a 2D reference frame (i.e., map), we present two aggregation techniques for 3D spatial and spatiotemporal data mapped onto virtual city models that hierarchically aggregate thematic data in real time during rendering to support on-the-fly and on-demand level-of-detail generation. An object-based technique performs aggregation based on scene-specific objects and their hierarchy to facilitate per-object analysis, while the scene-based technique aggregates data solely based on spatial locations, thus supporting visual analysis of data with arbitrary reference geometry. Both techniques can apply different aggregation functions (mean, minimum, and maximum) for ordinal, interval, and ratio-scaled data and can be easily extended with additional functions. Our implementation utilizes the programmable graphics pipeline and requires suitably encoded data, i.e., textures or vertex attributes. We demonstrate the application of both techniques using real-world datasets, including solar potential analyses and the propagation of pressure waves in a virtual city model. KW - Level-of-detail visualization KW - spatial aggregation KW - real-time rendering Y1 - 2018 U6 - https://doi.org/10.1145/3234506 SN - 2374-0353 SN - 2374-0361 VL - 4 IS - 3 PB - Association for Computing Machinery CY - New York ER - TY - THES A1 - Vogel, Thomas T1 - Model-driven engineering of self-adaptive software T1 - Modellgetriebene Entwicklung von Selbst-Adaptiver Software N2 - The development of self-adaptive software requires the engineering of an adaptation engine that controls the underlying adaptable software by a feedback loop. State-of-the-art approaches prescribe the feedback loop in terms of numbers, how the activities (e.g., monitor, analyze, plan, and execute (MAPE)) and the knowledge are structured to a feedback loop, and the type of knowledge. Moreover, the feedback loop is usually hidden in the implementation or framework and therefore not visible in the architectural design. Additionally, an adaptation engine often employs runtime models that either represent the adaptable software or capture strategic knowledge such as reconfiguration strategies. State-of-the-art approaches do not systematically address the interplay of such runtime models, which would otherwise allow developers to freely design the entire feedback loop. This thesis presents ExecUtable RuntimE MegAmodels (EUREMA), an integrated model-driven engineering (MDE) solution that rigorously uses models for engineering feedback loops. EUREMA provides a domain-specific modeling language to specify and an interpreter to execute feedback loops. The language allows developers to freely design a feedback loop concerning the activities and runtime models (knowledge) as well as the number of feedback loops. It further supports structuring the feedback loops in the adaptation engine that follows a layered architectural style. Thus, EUREMA makes the feedback loops explicit in the design and enables developers to reason about design decisions. To address the interplay of runtime models, we propose the concept of a runtime megamodel, which is a runtime model that contains other runtime models as well as activities (e.g., MAPE) working on the contained models. This concept is the underlying principle of EUREMA. The resulting EUREMA (mega)models are kept alive at runtime and they are directly executed by the EUREMA interpreter to run the feedback loops. Interpretation provides the flexibility to dynamically adapt a feedback loop. In this context, EUREMA supports engineering self-adaptive software in which feedback loops run independently or in a coordinated fashion within the same layer as well as on top of each other in different layers of the adaptation engine. Moreover, we consider preliminary means to evolve self-adaptive software by providing a maintenance interface to the adaptation engine. This thesis discusses in detail EUREMA by applying it to different scenarios such as single, multiple, and stacked feedback loops for self-repairing and self-optimizing the mRUBiS application. Moreover, it investigates the design and expressiveness of EUREMA, reports on experiments with a running system (mRUBiS) and with alternative solutions, and assesses EUREMA with respect to quality attributes such as performance and scalability. The conducted evaluation provides evidence that EUREMA as an integrated and open MDE approach for engineering self-adaptive software seamlessly integrates the development and runtime environments using the same formalism to specify and execute feedback loops, supports the dynamic adaptation of feedback loops in layered architectures, and achieves an efficient execution of feedback loops by leveraging incrementality. N2 - Die Entwicklung von selbst-adaptiven Softwaresystemen erfordert die Konstruktion einer geschlossenen Feedback Loop, die das System zur Laufzeit beobachtet und falls nötig anpasst. Aktuelle Konstruktionsverfahren schreiben eine bestimmte Feedback Loop im Hinblick auf Anzahl und Struktur vor. Die Struktur umfasst die vorhandenen Aktivitäten der Feedback Loop (z. B. Beobachtung, Analyse, Planung und Ausführung einer Adaption) und die Art des hierzu verwendeten Systemwissens. Dieses System- und zusätzlich das strategische Wissen (z. B. Adaptionsregeln) werden in der Regel in Laufzeitmodellen erfasst und in die Feedback Loop integriert. Aktuelle Verfahren berücksichtigen jedoch nicht systematisch die Laufzeitmodelle und deren Zusammenspiel, so dass Entwickler die Feedback Loop nicht frei entwerfen und gestalten können. Folglich wird die Feedback Loop während des Entwurfs der Softwarearchitektur häufig nicht explizit berücksichtigt. Diese Dissertation stellt mit EUREMA ein neues Konstruktionsverfahren für Feedback Loops vor. Basierend auf Prinzipien der modellgetriebenen Entwicklung (MDE) setzt EUREMA auf die konsequente Nutzung von Modellen für die Konstruktion, Ausführung und Adaption von selbst-adaptiven Softwaresystemen. Hierzu wird eine domänenspezifische Modellierungssprache (DSL) vorgestellt, mit der Entwickler die Feedback Loop frei entwerfen und gestalten können, d. h. ohne Einschränkung bezüglich der Aktivitäten, Laufzeitmodelle und Anzahl der Feedback Loops. Zusätzlich bietet die DSL eine Architektursicht auf das System, die die Feedback Loops berücksichtigt. Daher stellt die DSL Konstrukte zur Verfügung, mit denen Entwickler während des Entwurfs der Architektur die Feedback Loops explizit definieren und berücksichtigen können. Um das Zusammenspiel der Laufzeitmodelle zu erfassen, wird das Konzept eines sogenannten Laufzeitmegamodells vorgeschlagen, das alle Aktivitäten und Laufzeitmodelle einer Feedback Loop erfasst. Dieses Konzept dient als Grundlage der vorgestellten DSL. Die bei der Konstruktion und mit der DSL erzeugten (Mega-)Modelle werden zur Laufzeit bewahrt und von einem Interpreter ausgeführt, um das spezifizierte Adaptionsverhalten zu realisieren. Der Interpreteransatz bietet die notwendige Flexibilität, um das Adaptionsverhalten zur Laufzeit anzupassen. Dies ermöglicht über die Entwicklung von Systemen mit mehreren Feedback Loops auf einer Ebene hinaus das Schichten von Feedback Loops im Sinne einer adaptiven Regelung. Zusätzlich bietet EUREMA eine Schnittstelle für Wartungsprozesse an, um das Adaptionsverhalten im laufendem System anzupassen. Die Dissertation diskutiert den EUREMA-Ansatz und wendet diesen auf verschiedene Problemstellungen an, u. a. auf einzelne, mehrere und koordinierte als auch geschichtete Feedback Loops. Als Anwendungsbeispiel dient die Selbstheilung und Selbstoptimierung des Online-Marktplatzes mRUBiS. Für die Evaluierung von EUREMA werden Experimente mit dem laufenden mRUBiS und mit alternativen Lösungen durchgeführt, das Design und die Ausdrucksmächtigkeit der DSL untersucht und Qualitätsmerkmale wie Performanz und Skalierbarkeit betrachtet. Die Ergebnisse der Evaluierung legen nahe, dass EUREMA als integrierter und offener Ansatz für die Entwicklung selbst-adaptiver Softwaresysteme folgende Beiträge zum Stand der Technik leistet: eine nahtlose Integration der Entwicklungs- und Laufzeitumgebung durch die konsequente Verwendung von Modellen, die dynamische Anpassung des Adaptionsverhaltens in einer Schichtenarchitektur und eine effiziente Ausführung von Feedback Loops durch inkrementelle Verarbeitungsschritte. KW - model-driven engineering KW - self-adaptive software KW - domain-specific modeling KW - runtime models KW - software evolution KW - modellgetriebene Entwicklung KW - Selbst-Adaptive Software KW - Domänenspezifische Modellierung KW - Laufzeitmodelle KW - Software-Evolution Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-409755 ER - TY - THES A1 - Vitagliano, Gerardo T1 - Modeling the structure of tabular files for data preparation T1 - Modellierung der Struktur von Tabellarische Dateien für die Datenaufbereitung N2 - To manage tabular data files and leverage their content in a given downstream task, practitioners often design and execute complex transformation pipelines to prepare them. The complexity of such pipelines stems from different factors, including the nature of the preparation tasks, often exploratory or ad-hoc to specific datasets; the large repertory of tools, algorithms, and frameworks that practitioners need to master; and the volume, variety, and velocity of the files to be prepared. Metadata plays a fundamental role in reducing this complexity: characterizing a file assists end users in the design of data preprocessing pipelines, and furthermore paves the way for suggestion, automation, and optimization of data preparation tasks. Previous research in the areas of data profiling, data integration, and data cleaning, has focused on extracting and characterizing metadata regarding the content of tabular data files, i.e., about the records and attributes of tables. Content metadata are useful for the latter stages of a preprocessing pipeline, e.g., error correction, duplicate detection, or value normalization, but they require a properly formed tabular input. Therefore, these metadata are not relevant for the early stages of a preparation pipeline, i.e., to correctly parse tables out of files. In this dissertation, we turn our focus to what we call the structure of a tabular data file, i.e., the set of characters within a file that do not represent data values but are required to parse and understand the content of the file. We provide three different approaches to represent file structure, an explicit representation based on context-free grammars; an implicit representation based on file-wise similarity; and a learned representation based on machine learning. In our first contribution, we use the grammar-based representation to characterize a set of over 3000 real-world csv files and identify multiple structural issues that let files deviate from the csv standard, e.g., by having inconsistent delimiters or containing multiple tables. We leverage our learnings about real-world files and propose Pollock, a benchmark to test how well systems parse csv files that have a non-standard structure, without any previous preparation. We report on our experiments on using Pollock to evaluate the performance of 16 real-world data management systems. Following, we characterize the structure of files implicitly, by defining a measure of structural similarity for file pairs. We design a novel algorithm to compute this measure, which is based on a graph representation of the files' content. We leverage this algorithm and propose Mondrian, a graphical system to assist users in identifying layout templates in a dataset, classes of files that have the same structure, and therefore can be prepared by applying the same preparation pipeline. Finally, we introduce MaGRiTTE, a novel architecture that uses self-supervised learning to automatically learn structural representations of files in the form of vectorial embeddings at three different levels: cell level, row level, and file level. We experiment with the application of structural embeddings for several tasks, namely dialect detection, row classification, and data preparation efforts estimation. Our experimental results show that structural metadata, either identified explicitly on parsing grammars, derived implicitly as file-wise similarity, or learned with the help of machine learning architectures, is fundamental to automate several tasks, to scale up preparation to large quantities of files, and to provide repeatable preparation pipelines. N2 - Anwender müssen häufig komplexe Pipelines zur Aufbereitung von tabellarischen Dateien entwerfen, um diese verwalten und ihre Inhalte für nachgelagerte Aufgaben nutzen zu können. Die Komplexität solcher Pipelines ergibt sich aus verschiedenen Faktoren, u.a. (i) aus der Art der Aufbereitungsaufgaben, die oft explorativ oder ad hoc für bestimmte Datensätze durchgeführt werden, (ii) aus dem großen Repertoire an Werkzeugen, Algorithmen und Frameworks, die von den Anwendern beherrscht werden müssen, sowie (iii) aus der Menge, der Größe und der Verschiedenartigkeit der aufzubereitenden Dateien. Metadaten spielen eine grundlegende Rolle bei der Verringerung dieser Komplexität: Die Charakterisierung einer Datei hilft den Nutzern bei der Gestaltung von Datenaufbereitungs-Pipelines und ebnet darüber hinaus den Weg für Vorschläge, Automatisierung und Optimierung von Datenaufbereitungsaufgaben. Bisherige Forschungsarbeiten in den Bereichen Data Profiling, Datenintegration und Datenbereinigung konzentrierten sich auf die Extraktion und Charakterisierung von Metadaten über die Inhalte der tabellarischen Dateien, d.h. über die Datensätze und Attribute von Tabellen. Inhalts-basierte Metadaten sind für die letzten Phasen einer Aufbereitungspipeline nützlich, z.B. für die Fehlerkorrektur, die Erkennung von Duplikaten oder die Normalisierung von Werten, aber sie erfordern eine korrekt geformte tabellarische Eingabe. Daher sind diese Metadaten für die frühen Phasen einer Aufbereitungspipeline, d.h. für das korrekte Parsen von Tabellen aus Dateien, nicht relevant. In dieser Dissertation konzentrieren wir uns die Struktur einer tabellarischen Datei nennen, d.h. die Menge der Zeichen in einer Datei, die keine Datenwerte darstellen, aber erforderlich sind, um den Inhalt der Datei zu analysieren und zu verstehen. Wir stellen drei verschiedene Ansätze zur Darstellung der Dateistruktur vor: eine explizite Darstellung auf der Grundlage kontextfreier Grammatiken, eine implizite Darstellung auf der Grundlage von Dateiähnlichkeiten und eine erlernte Darstellung auf der Grundlage von maschinellem Lernen. In unserem ersten Ansatz verwenden wir die grammatikbasierte Darstellung, um eine Menge von über 3000 realen CSV-Dateien zu charakterisieren und mehrere strukturelle Probleme zu identifizieren, die dazu führen, dass Dateien vom CSV-Standard abweichen, z.B. durch inkonsistente Begrenzungszeichen oder dem Enthalten mehrere Tabellen in einer einzelnen Datei. Wir nutzen unsere Erkenntnisse aus realen Dateien und schlagen Pollock vor, einen Benchmark, der testet, wie gut Systeme unaufbereitete CSV-Dateien parsen. Wir berichten über unsere Experimente zur Verwendung von Pollock, in denen wir die Leistung von 16 realen Datenverwaltungssystemen bewerten. Anschließend charakterisieren wir die Struktur von Dateien implizit, indem wir ein Maß für die strukturelle Ähnlichkeit von Dateipaaren definieren. Wir entwickeln einen neuartigen Algorithmus zur Berechnung dieses Maßes, der auf einer Graphen-basierten Darstellung des Dateiinhalts basiert. Wir nutzen diesen Algorithmus und schlagen Mondrian vor, ein grafisches System zur Unterstützung der Benutzer bei der Identifizierung von Layout Vorlagen in einem Datensatz, d.h. von Dateiklassen, die die gleiche Struktur aufweisen und daher mit der gleichen Pipeline aufbereitet werden können. Schließlich stellen wir MaGRiTTE vor, eine neuartige Architektur, die selbst- überwachtes Lernen verwendet, um automatisch strukturelle Darstellungen von Dateien in Form von vektoriellen Einbettungen auf drei verschiedenen Ebenen zu lernen: auf Zellebene, auf Zeilenebene und auf Dateiebene. Wir experimentieren mit der Anwendung von strukturellen Einbettungen für verschiedene Aufgaben, nämlich Dialekterkennung, Zeilenklassifizierung und der Schätzung des Aufwands für die Datenaufbereitung. Unsere experimentellen Ergebnisse zeigen, dass strukturelle Metadaten, die entweder explizit mit Hilfe von Parsing-Grammatiken identifiziert, implizit als Dateiähnlichkeit abgeleitet oder mit Machine-Learning Architekturen erlernt werden, von grundlegender Bedeutung für die Automatisierung verschiedener Aufgaben, die Skalierung der Aufbereitung auf große Mengen von Dateien und die Bereitstellung wiederholbarer Aufbereitungspipelines sind. KW - data preparation KW - file structure KW - Datenaufbereitung KW - tabellarische Dateien KW - Dateistruktur KW - tabular data Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-624351 ER - TY - JOUR A1 - Van Hout, Cristopher V. A1 - Tachmazidou, Ioanna A1 - Backman, Joshua D. A1 - Hoffman, Joshua D. A1 - Liu, Daren A1 - Pandey, Ashutosh K. A1 - Gonzaga-Jauregui, Claudia A1 - Khalid, Shareef A1 - Ye, Bin A1 - Banerjee, Nilanjana A1 - Li, Alexander H. A1 - O'Dushlaine, Colm A1 - Marcketta, Anthony A1 - Staples, Jeffrey A1 - Schurmann, Claudia A1 - Hawes, Alicia A1 - Maxwell, Evan A1 - Barnard, Leland A1 - Lopez, Alexander A1 - Penn, John A1 - Habegger, Lukas A1 - Blumenfeld, Andrew L. A1 - Bai, Xiaodong A1 - O'Keeffe, Sean A1 - Yadav, Ashish A1 - Praveen, Kavita A1 - Jones, Marcus A1 - Salerno, William J. A1 - Chung, Wendy K. A1 - Surakka, Ida A1 - Willer, Cristen J. A1 - Hveem, Kristian A1 - Leader, Joseph B. A1 - Carey, David J. A1 - Ledbetter, David H. A1 - Cardon, Lon A1 - Yancopoulos, George D. A1 - Economides, Aris A1 - Coppola, Giovanni A1 - Shuldiner, Alan R. A1 - Balasubramanian, Suganthi A1 - Cantor, Michael A1 - Nelson, Matthew R. A1 - Whittaker, John A1 - Reid, Jeffrey G. A1 - Marchini, Jonathan A1 - Overton, John D. A1 - Scott, Robert A. A1 - Abecasis, Goncalo R. A1 - Yerges-Armstrong, Laura M. A1 - Baras, Aris T1 - Exome sequencing and characterization of 49,960 individuals in the UK Biobank JF - Nature : the international weekly journal of science N2 - The UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world(1). Here we describe the release of exome-sequence data for the first 49,960 study participants, revealing approximately 4 million coding variants (of which around 98.6% have a frequency of less than 1%). The data include 198,269 autosomal predicted loss-of-function (LOF) variants, a more than 14-fold increase compared to the imputed sequence. Nearly all genes (more than 97%) had at least one carrier with a LOF variant, and most genes (more than 69%) had at least ten carriers with a LOF variant. We illustrate the power of characterizing LOF variants in this population through association analyses across 1,730 phenotypes. In addition to replicating established associations, we found novel LOF variants with large effects on disease traits, includingPIEZO1on varicose veins,COL6A1on corneal resistance,MEPEon bone density, andIQGAP2andGMPRon blood cell traits. We further demonstrate the value of exome sequencing by surveying the prevalence of pathogenic variants of clinical importance, and show that 2% of this population has a medically actionable variant. Furthermore, we characterize the penetrance of cancer in carriers of pathogenicBRCA1andBRCA2variants. Exome sequences from the first 49,960 participants highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community.
Exome sequences from the first 49,960 participants in the UK Biobank highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community. KW - clinical exome KW - breast-cancer KW - mutations KW - recommendations KW - gene KW - metaanalysis KW - variants, KW - BRCA1 KW - risk KW - susceptibility Y1 - 2020 U6 - https://doi.org/10.1038/s41586-020-2853-0 SN - 0028-0836 SN - 1476-4687 VL - 586 IS - 7831 SP - 749 EP - 756 PB - Macmillan Publishers Limited CY - London ER - TY - JOUR A1 - van Esveld, Selma A1 - de Vries, Nardo A1 - Becchetti, Sibilla A1 - Dopper, Sofia A1 - van Valkenburg, Willem ED - Meinel, Christoph ED - Schweiger, Stefanie ED - Staubitz, Thomas ED - Conrad, Robert ED - Alario Hoyos, Carlos ED - Ebner, Martin ED - Sancassani, Susanna ED - Żur, Agnieszka ED - Friedl, Christian ED - Halawa, Sherif ED - Gamage, Dilrukshi ED - Cross, Jeffrey ED - Kristine Jonson Carlon, May ED - Deville, Yves ED - Gaebel, Michael ED - Delgado Kloos, Carlos ED - von Schmieden, Karen T1 - Impact of Mooc and Other Online Course Development on Campus Education JF - EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash? N2 - The TU Delft Extension School for Continuing Education develops and delivers MOOCs, programs and other online courses for lifelong learners and professionals worldwide focused on Science, Engineering & Design. At the beginning of 2022, we started a project to examine whether creating an online course had any impact on TU Delft campus education. Through a survey, we collected feedback from 68 TU Delft lecturers involved in developing and offering online courses and programs for lifelong learners and professionals. The lecturers reported on the impact of developing an online course on a personal and curricular level. The results showed that the developed online materials, and the acquired skills and experiences from creating online courses, were beneficial for campus education, especially during the transition to remote emergency teaching in the COVID-19 lockdown periods. In this short paper, we will describe the responses in detail and map the benefits and challenges experienced by lecturers when implementing their online course materials and newly acquired educational skills on campus. Finally, we will explore future possibilities to extend the reported, already relevant, impact of MOOCs and of other online courses on campus education. KW - Digitale Bildung KW - Kursdesign KW - MOOC KW - Micro Degree KW - Online-Lehre KW - Onlinekurs KW - Onlinekurs-Produktion KW - digital education KW - e-learning KW - micro degree KW - micro-credential KW - online course creation KW - online course design KW - online teaching Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-620785 SP - 1 EP - 8 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - BOOK A1 - van der Walt, Estee A1 - Odun-Ayo, Isaac A1 - Bastian, Matthias A1 - Eldin Elsaid, Mohamed Esam T1 - Proceedings of the Fifth HPI Cloud Symposium "Operating the Cloud“ 2017 N2 - Every year, the Hasso Plattner Institute (HPI) invites guests from industry and academia to a collaborative scientific workshop on the topic Operating the Cloud. Our goal is to provide a forum for the exchange of knowledge and experience between industry and academia. Co-located with the event is the HPI’s Future SOC Lab day, which offers an additional attractive and conducive environment for scientific and industry related discussions. Operating the Cloud aims to be a platform for productive interactions of innovative ideas, visions, and upcoming technologies in the field of cloud operation and administration. In these proceedings, the results of the fifth HPI cloud symposium Operating the Cloud 2017 are published. We thank the authors for exciting presentations and insights into their current work and research. Moreover, we look forward to more interesting submissions for the upcoming symposium in 2018. N2 - Jedes Jahr lädt das Hasso-Plattner-Institut (HPI) Gäste aus der Industrie und der Wissenschaft zu einem kooperativen und wissenschaftlichen Symposium zum Thema Cloud Computing ein. Unser Ziel ist es, ein Forum für den Austausch von Wissen und Erfahrungen zwischen der Industrie und der Wissenschaft zu bieten. Parallel zur Veranstaltung findet der HPI Future SOC Lab Tag statt, der eine zusätzliche attraktive Umgebung für wissenschaftliche und branchenbezogene Diskussionen bietet. Das Symposium zielt darauf ab, eine Plattform für produktive Interaktionen von innovativen Ideen, Visionen und aufkommenden Technologien im Bereich von Cloud Computing zu bitten. Anlässlich dieses Symposiums fordern wir die Einreichung von Forschungsarbeiten und Erfahrungsberichte. Dieser technische Bericht umfasst eine Zusammenstellung der im Rahmen des fünften HPI Cloud Symposiums "Operating the Cloud" 2017 angenommenen Forschungspapiere. Wir danken den Autoren für spannende Vorträge und Einblicke in ihre aktuelle Arbeit und Forschung. Darüber hinaus freuen wir uns auf weitere interessante Einreichungen für das kommende Symposium im Laufe des Jahres. T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 122 KW - Sicherheit KW - verteilte Leistungsüberwachung KW - Identitätsmanagement KW - Leistungsmodelle von virtuellen Maschinen KW - Privatsphäre KW - security KW - distributed performance monitoring KW - identity management KW - performance models of virtual machines KW - privacy Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-411330 SN - 978-3-86956-432-6 SN - 1613-5652 SN - 2191-1665 IS - 122 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - van der Aa, Han A1 - Leopold, Henrik A1 - Weidlich, Matthias T1 - Partial order resolution of event logs for process conformance checking JF - Decision support systems : DSS N2 - While supporting the execution of business processes, information systems record event logs. Conformance checking relies on these logs to analyze whether the recorded behavior of a process conforms to the behavior of a normative specification. A key assumption of existing conformance checking techniques, however, is that all events are associated with timestamps that allow to infer a total order of events per process instance. Unfortunately, this assumption is often violated in practice. Due to synchronization issues, manual event recordings, or data corruption, events are only partially ordered. In this paper, we put forward the problem of partial order resolution of event logs to close this gap. It refers to the construction of a probability distribution over all possible total orders of events of an instance. To cope with the order uncertainty in real-world data, we present several estimators for this task, incorporating different notions of behavioral abstraction. Moreover, to reduce the runtime of conformance checking based on partial order resolution, we introduce an approximation method that comes with a bounded error in terms of accuracy. Our experiments with real-world and synthetic data reveal that our approach improves accuracy over the state-of-the-art considerably. KW - process mining KW - conformance checking KW - partial order resolution KW - data KW - uncertainty Y1 - 2020 U6 - https://doi.org/10.1016/j.dss.2020.113347 SN - 0167-9236 SN - 1873-5797 VL - 136 PB - Elsevier CY - Amsterdam [u.a.] ER - TY - JOUR A1 - Utunen, Heini A1 - Attias, Melissa ED - Meinel, Christoph ED - Schweiger, Stefanie ED - Staubitz, Thomas ED - Conrad, Robert ED - Alario Hoyos, Carlos ED - Ebner, Martin ED - Sancassani, Susanna ED - Żur, Agnieszka ED - Friedl, Christian ED - Halawa, Sherif ED - Gamage, Dilrukshi ED - Scott, Jeffrey ED - Kristine Jonson Carlon, May ED - Deville, Yves ED - Gaebel, Michael ED - Delgado Kloos, Carlos ED - von Schmieden, Karen T1 - xMOOCs BT - modality for mass reach during the pandemic for the World Health Organization JF - EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash? N2 - The World Health Organization designed OpenWHO.org to provide an inclusive and accessible online environment to equip learners across the globe with critical up-to-date information and to be able to effectively protect themselves in health emergencies. The platform thus focuses on the eXtended Massive Open Online Course (xMOOC) modality – contentfocused and expert-driven, one-to-many modelled, and self-paced for scalable learning. In this paper, we describe how OpenWHO utilized xMOOCs to reach mass audiences during the COVID-19 pandemic; the paper specifically examines the accessibility, language inclusivity and adaptability of hosted xMOOCs. As of February 2023, OpenWHO had 7.5 million enrolments across 200 xMOOCs on health emergency, epidemic, pandemic and other public health topics available across 65 languages, including 46 courses targeted for the COVID-19 pandemic. Our results suggest that the xMOOC modality allowed OpenWHO to expand learning during the pandemic to previously underrepresented groups, including women, participants ages 70 and older, and learners younger than age 20. The OpenWHO use case shows that xMOOCs should be considered when there is a need for massive knowledge transfer in health emergency situations, yet the approach should be context-specific according to the type of health emergency, targeted population and region. Our evidence also supports previous calls to put intervention elements that contribute to removing barriers to access at the core of learning and health information dissemination. Equity must be the fundamental principle and organizing criteria for public health work. KW - Digitale Bildung KW - Kursdesign KW - MOOC KW - Micro Degree KW - Online-Lehre KW - Onlinekurs KW - Onlinekurs-Produktion KW - digital education KW - e-learning KW - micro degree KW - micro-credential KW - online course creation KW - online course design KW - online teaching Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-624788 SP - 279 EP - 289 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - THES A1 - Ussath, Martin Georg T1 - Analytical approaches for advanced attacks Y1 - 2017 ER - TY - JOUR A1 - Ulrich, Jens-Uwe A1 - Lutfi, Ahmad A1 - Rutzen, Kilian A1 - Renard, Bernhard Y. T1 - ReadBouncer BT - precise and scalable adaptive sampling for nanopore sequencing JF - Bioinformatics N2 - Motivation: Nanopore sequencers allow targeted sequencing of interesting nucleotide sequences by rejecting other sequences from individual pores. This feature facilitates the enrichment of low-abundant sequences by depleting overrepresented ones in-silico. Existing tools for adaptive sampling either apply signal alignment, which cannot handle human-sized reference sequences, or apply read mapping in sequence space relying on fast graphical processing units (GPU) base callers for real-time read rejection. Using nanopore long-read mapping tools is also not optimal when mapping shorter reads as usually analyzed in adaptive sampling applications. Results: Here, we present a new approach for nanopore adaptive sampling that combines fast CPU and GPU base calling with read classification based on Interleaved Bloom Filters. ReadBouncer improves the potential enrichment of low abundance sequences by its high read classification sensitivity and specificity, outperforming existing tools in the field. It robustly removes even reads belonging to large reference sequences while running on commodity hardware without GPUs, making adaptive sampling accessible for in-field researchers. Readbouncer also provides a user-friendly interface and installer files for end-users without a bioinformatics background. Y1 - 2022 U6 - https://doi.org/10.1093/bioinformatics/btac223 SN - 1367-4803 SN - 1460-2059 VL - 38 IS - SUPPL 1 SP - 153 EP - 160 PB - Oxford Univ. Press CY - Oxford ER - TY - GEN A1 - Ullrich, Andre A1 - Enke, Judith A1 - Teichmann, Malte A1 - Kress, Antonio A1 - Gronau, Norbert T1 - Audit - and then what? BT - a roadmap for digitization of learning factories T2 - Procedia Manufacturing N2 - Current trends such as digital transformation, Internet of Things, or Industry 4.0 are challenging the majority of learning factories. Regardless of whether a conventional learning factory, a model factory, or a digital learning factory, traditional approaches such as the monotonous execution of specific instructions don‘t suffice the learner’s needs, market requirements as well as especially current technological developments. Contemporary teaching environments need a clear strategy, a road to follow for being able to successfully cope with the changes and develop towards digitized learning factories. This demand driven necessity of transformation leads to another obstacle: Assessing the status quo and developing and implementing adequate action plans. Within this paper, details of a maturity-based audit of the hybrid learning factory in the Research and Application Centre Industry 4.0 and a thereof derived roadmap for the digitization of a learning factory are presented. KW - Audit KW - Digitization KW - Learning Factory KW - Roadmap Y1 - 2019 U6 - https://doi.org/10.1016/j.promfg.2019.03.025 SN - 2351-9789 VL - 31 SP - 162 EP - 168 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Trilla, Irene A1 - Drimalla, Hanna A1 - Bajbouj, Malek A1 - Dziobek, Isabel T1 - The influence of reward on facial mimicry BT - no evidence for a significant effect of oxytocin JF - Frontiers in behavioral neuroscience N2 - Recent findings suggest a role of oxytocin on the tendency to spontaneously mimic the emotional facial expressions of others. Oxytocin-related increases of facial mimicry, however, seem to be dependent on contextual factors. Given previous literature showing that people preferentially mimic emotional expressions of individuals associated with high (vs. low) rewards, we examined whether the reward value of the mimicked agent is one factor influencing the oxytocin effects on facial mimicry. To test this hypothesis, 60 male adults received 24 IU of either intranasal oxytocin or placebo in a double-blind, between-subject experiment. Next, the value of male neutral faces was manipulated using an associative learning task with monetary rewards. After the reward associations were learned, participants watched videos of the same faces displaying happy and angry expressions. Facial reactions to the emotional expressions were measured with electromyography. We found that participants judged as more pleasant the face identities associated with high reward values than with low reward values. However, happy expressions by low rewarding faces were more spontaneously mimicked than high rewarding faces. Contrary to our expectations, we did not find a significant direct effect of intranasal oxytocin on facial mimicry, nor on the reward-driven modulation of mimicry. Our results support the notion that mimicry is a complex process that depends on contextual factors, but failed to provide conclusive evidence of a role of oxytocin on the modulation of facial mimicry. KW - oxytocin KW - facial mimicry KW - reward KW - EMG KW - social modulation KW - null results Y1 - 2020 U6 - https://doi.org/10.3389/fnbeh.2020.00088 SN - 1662-5153 VL - 14 PB - Frontiers Media CY - Lausanne ER - TY - JOUR A1 - Trautmann, Justin A1 - Zhou, Lin A1 - Brahms, Clemens Markus A1 - Tunca, Can A1 - Ersoy, Cem A1 - Granacher, Urs A1 - Arnrich, Bert T1 - TRIPOD BT - A treadmill walking dataset with IMU, pressure-distribution and photoelectric data for gait analysis JF - Data : open access ʻData in scienceʼ journal N2 - Inertial measurement units (IMUs) enable easy to operate and low-cost data recording for gait analysis. When combined with treadmill walking, a large number of steps can be collected in a controlled environment without the need of a dedicated gait analysis laboratory. In order to evaluate existing and novel IMU-based gait analysis algorithms for treadmill walking, a reference dataset that includes IMU data as well as reliable ground truth measurements for multiple participants and walking speeds is needed. This article provides a reference dataset consisting of 15 healthy young adults who walked on a treadmill at three different speeds. Data were acquired using seven IMUs placed on the lower body, two different reference systems (Zebris FDMT-HQ and OptoGait), and two RGB cameras. Additionally, in order to validate an existing IMU-based gait analysis algorithm using the dataset, an adaptable modular data analysis pipeline was built. Our results show agreement between the pressure-sensitive Zebris and the photoelectric OptoGait system (r = 0.99), demonstrating the quality of our reference data. As a use case, the performance of an algorithm originally designed for overground walking was tested on treadmill data using the data pipeline. The accuracy of stride length and stride time estimations was comparable to that reported in other studies with overground data, indicating that the algorithm is equally applicable to treadmill data. The Python source code of the data pipeline is publicly available, and the dataset will be provided by the authors upon request, enabling future evaluations of IMU gait analysis algorithms without the need of recording new data. KW - inertial measurement unit KW - gait analysis algorithm KW - OptoGait KW - Zebris KW - data pipeline KW - public dataset Y1 - 2021 U6 - https://doi.org/10.3390/data6090095 SN - 2306-5729 VL - 6 IS - 9 PB - MDPI CY - Basel ER - TY - GEN A1 - Trautmann, Justin A1 - Zhou, Lin A1 - Brahms, Clemens Markus A1 - Tunca, Can A1 - Ersoy, Cem A1 - Granacher, Urs A1 - Arnrich, Bert T1 - TRIPOD - A Treadmill Walking Dataset with IMU, Pressure-distribution and Photoelectric Data for Gait Analysis T2 - Postprints der Universität Potsdam : Reihe der Digital Engineering Fakultät N2 - Inertial measurement units (IMUs) enable easy to operate and low-cost data recording for gait analysis. When combined with treadmill walking, a large number of steps can be collected in a controlled environment without the need of a dedicated gait analysis laboratory. In order to evaluate existing and novel IMU-based gait analysis algorithms for treadmill walking, a reference dataset that includes IMU data as well as reliable ground truth measurements for multiple participants and walking speeds is needed. This article provides a reference dataset consisting of 15 healthy young adults who walked on a treadmill at three different speeds. Data were acquired using seven IMUs placed on the lower body, two different reference systems (Zebris FDMT-HQ and OptoGait), and two RGB cameras. Additionally, in order to validate an existing IMU-based gait analysis algorithm using the dataset, an adaptable modular data analysis pipeline was built. Our results show agreement between the pressure-sensitive Zebris and the photoelectric OptoGait system (r = 0.99), demonstrating the quality of our reference data. As a use case, the performance of an algorithm originally designed for overground walking was tested on treadmill data using the data pipeline. The accuracy of stride length and stride time estimations was comparable to that reported in other studies with overground data, indicating that the algorithm is equally applicable to treadmill data. The Python source code of the data pipeline is publicly available, and the dataset will be provided by the authors upon request, enabling future evaluations of IMU gait analysis algorithms without the need of recording new data. T3 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät - 6 KW - inertial measurement unit KW - gait analysis algorithm KW - OptoGait KW - Zebris KW - data pipeline KW - public dataset Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-522027 IS - 6 ER - TY - THES A1 - Traifeh, Hanadi T1 - Design Thinking in the Arab world T1 - Design Thinking in der Arabischen Welt BT - perspectives, challenges and opportunities BT - Perspektiven, Herausforderungen und Potentiale N2 - Design Thinking is a human-centered approach to innovation that has become increasingly popular globally over the last decade. While the spread of Design Thinking is well understood and documented in the Western cultural contexts, particularly in Europe and the US due to the popularity of the Stanford-Potsdam Design Thinking education model, this is not the case when it comes to non-Western cultural contexts. This thesis fills a gap identified in the literature regarding how Design Thinking emerged, was perceived, adopted, and practiced in the Arab world. The culture in that part of the world differs from that of the Western context, which impacts the mindset of people and how they interact with Design Thinking tools and methods. A mixed-methods research approach was followed in which both quantitative and qualitative methods were employed. First, two methods were used in the quantitative phase: a social media analysis using Twitter as a source of data, and an online questionnaire. The results and analysis of the quantitative data informed the design of the qualitative phase in which two methods were employed: ten semi-structured interviews, and participant observation of seven Design Thinking training events. According to the analyzed data, the Arab world appears to have had an early, though relatively weak, and slow, adoption of Design Thinking since 2006. Increasing adoption, however, has been witnessed over the last decade, especially in Saudi Arabia, the United Arab Emirates and Egypt. The results also show that despite its limited spread, Design Thinking has been practiced the most in education, information technology and communication, administrative services, and the non-profit sectors. The way it is being practiced, though, is not fully aligned with how it is being practiced and taught in the US and Europe, as most people in the region do not necessarily believe in all mindset attributes introduced by the Stanford-Potsdam tradition. Practitioners in the Arab world also seem to shy away from the 'wild side' of Design Thinking in particular, and do not fully appreciate the connection between art-design, and science-engineering. This questions the role of the educational institutions in the region since -according to the findings- they appear to be leading the movement in promoting and developing Design Thinking in the Arab world. Nonetheless, it is notable that people seem to be aware of the positive impact of applying Design Thinking in the region, and its potential to bring meaningful transformation. However, they also seem to be concerned about the current cultural, social, political, and economic challenges that may challenge this transformation. Therefore, they call for more awareness and demand to create Arabic, culturally appropriate programs to respond to the local needs. On another note, the lack of Arabic content and local case studies on Design Thinking were identified by several interviewees and were also confirmed by the participant observation as major challenges that are slowing down the spread of Design Thinking or sometimes hampering capacity building in the region. Other challenges that were revealed by the study are: changing the mindset of people, the lack of dedicated Design Thinking spaces, and the need for clear instructions on how to apply Design Thinking methods and activities. The concept of time and how Arabs deal with it, gender management during trainings, and hierarchy and power dynamics among training participants are also among the identified challenges. Another key finding revealed by the study is the confirmation of التفكير التصميمي as the Arabic term to be most widely adopted in the region to refer to Design Thinking, since four other Arabic terms were found to be associated with Design Thinking. Based on the findings of the study, the thesis concludes by presenting a list of recommendations on how to overcome the mentioned challenges and what factors should be considered when designing and implementing culturally-customized Design Thinking training in the Arab region. N2 - Design Thinking ist ein nutzerzentrierter Innovationsansatz, der in den letzten zehn Jahren weltweit an Bekanntheit gewonnen hat. Während die Verbreitung von Design Thinking im westlichen Kulturkreis – insbesondere in Europa und den USA – aufgrund der Bedeutung des Stanford-Potsdam Design Thinking-Ausbildungsmodells gut verstanden und dokumentiert ist, ist dies nicht der Fall, wenn es sich um nicht-westliche Kulturkreise handelt. Diese Arbeit schließt eine Lücke in der Literatur darüber, wie Design Thinking in der arabischen Welt entstanden ist, wahrgenommen, angenommen und praktiziert wurde. Die vorhandenen kulturellen Unterschiede zwischen der westlichen und der arabischen Welt wirken sich auch auf die Denkweise der Menschen aus, unddarauf, wie sie mit Design Thinking-Tools und -Methoden umgehen. Es wurde ein ‚Mixed Methods‘-Forschungsansatz verfolgt, d.h. sowohl quantitative als auch qualitative Methoden wurden eingesetzt. In der quantitativen Phase kamen zunächst zwei Methoden zum Einsatz: eine Social-Media-Analyse mit Twitter als Datenquelle und ein Online-Fragebogen. Die Ergebnisse und die Analyse der quantitativen Daten bildeten die Grundlage für die Gestaltung der qualitativen Phase, in der zwei Methoden angewendet wurden: zehn halbstrukturierte Interviews und die teilnehmende Beobachtung von sieben Design Thinking-Trainings. Den analysierten Daten zufolge scheint es in der arabischen Welt seit 2006 eine frühe, wenn auch relativ schwache und langsame Einführung von Design Thinking gegeben zu haben. In den letzten zehn Jahren ist jedoch eine zunehmende Akzeptanz zu beobachten, insbesondere in Saudi-Arabien, den Vereinigten Arabischen Emiraten und Ägypten. Die Ergebnisse zeigen auch, dass Design Thinking trotz seiner begrenzten Verbreitung am häufigsten im Bildungswesen, in der Informationstechnologie und Kommunikation, in der Verwaltung und im Non-Profit-Sektor angewandt wird. Die Art und Weise, wie Design Thinking praktiziert wird, stimmt jedoch nicht vollständig mit der Art und Weise überein, wie es in den USA und Europa praktiziert und gelehrt wird, da die meisten Menschen in der Region nicht unbedingt an alle Denkattribute glauben, die im Stanford-Potsdam-Modell eingeführt wurden. Die Praktiker in der arabischen Welt scheinen auch vor der "wilden Seite" des Design Thinking zurückzuschrecken und die Verbindung zwischen Kunst und Design auf der einen sowie Wissenschaft und Technik auf der anderen Seite nicht vollumfänglich zu schätzen. Dies wirft die Frage nach der Rolle von Bildungseinrichtungen in der Region auf, da sie - den Ergebnissen zufolge - die Bewegung zur Förderung und Entwicklung von Design Thinking in der arabischen Welt anzuführen scheinen. Nichtsdestotrotz ist es bemerkenswert, dass sich die Menschen der positiven Auswirkungen der Anwendung von Design Thinking in der Region und seines Potenzials, sinnvolle Veränderungen zu bewirken, bewusst zu sein scheinen. Sie scheinen jedoch auch besorgt zu sein über die aktuellen kulturellen, sozialen, politischen und wirtschaftlichen Herausforderungen, die diese Transformation in Frage stellen könnten. Daher fordern sie eine stärkere Sensibilisierung und die Schaffung von arabischen, kulturell angemessenen Programmen, um auf die lokalen Bedürfnisse einzugehen. Auch das Fehlen arabischer Inhalte und lokaler Fallstudien zu Design Thinking wurde von mehreren Befragten genannt und durch die teilnehmende Beobachtung bestätigt, da dies die Verbreitung von Design Thinking verlangsamt oder den Aufbau von Kapazitäten in der Region behindert. Weitere Herausforderungen, die sich aus der Studie ergaben, sind: die Veränderung des Mindsets der Menschen, das Fehlen spezieller Design-Thinking-Räume und der Bedarf an klaren Anweisungen zur Anwendung von Design-Thinking-Methoden und -Aktivitäten. Das Konzept von Zeit und der Umgang der arabischen Welt damit, Gender-Management während der Schulungen sowie Hierarchie und Machtdynamik unter den Schulungsteilnehmern gehören ebenfalls zu den identifizierten Herausforderungen. Ein weiteres wichtiges Ergebnis der Studie ist die Bestätigung von التفكير التصميمي als dem in der Region am weitesten verbreiteten arabischen Begriff für Design Thinking, da vier weitere arabische Begriffe mit Design Thinking in Verbindung gebracht werden konnten. Basierend auf den Ergebnissen der Studie schließt die Arbeit mit einer Liste von Empfehlungen, wie die genannten Herausforderungen überwunden werden können und welche Faktoren bei der Entwicklung und Implementierung von kulturell angepassten Design Thinking-Trainings in der arabischen Welt berücksichtigt werden sollten. KW - Design Thinking KW - human-centered design KW - the Arab world KW - emergence KW - adoption KW - implementation KW - culture KW - Design Thinking KW - Annahme KW - Kultur KW - Entstehung KW - menschenzentriertes Design KW - Implementierung KW - die arabische Welt Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-598911 ER - TY - GEN A1 - Torkura, Kennedy A. A1 - Sukmana, Muhammad Ihsan Haikal A1 - Strauss, Tim A1 - Graupner, Hendrik A1 - Cheng, Feng A1 - Meinel, Christoph T1 - CSBAuditor BT - proactive security risk analysis for cloud storage broker systems T2 - 17th International Symposium on Network Computing and Applications (NCA) N2 - Cloud Storage Brokers (CSB) provide seamless and concurrent access to multiple Cloud Storage Services (CSS) while abstracting cloud complexities from end-users. However, this multi-cloud strategy faces several security challenges including enlarged attack surfaces, malicious insider threats, security complexities due to integration of disparate components and API interoperability issues. Novel security approaches are imperative to tackle these security issues. Therefore, this paper proposes CSBAuditor, a novel cloud security system that continuously audits CSB resources, to detect malicious activities and unauthorized changes e.g. bucket policy misconfigurations, and remediates these anomalies. The cloud state is maintained via a continuous snapshotting mechanism thereby ensuring fault tolerance. We adopt the principles of chaos engineering by integrating Broker Monkey, a component that continuously injects failure into our reference CSB system, Cloud RAID. Hence, CSBAuditor is continuously tested for efficiency i.e. its ability to detect the changes injected by Broker Monkey. CSBAuditor employs security metrics for risk analysis by computing severity scores for detected vulnerabilities using the Common Configuration Scoring System, thereby overcoming the limitation of insufficient security metrics in existing cloud auditing schemes. CSBAuditor has been tested using various strategies including chaos engineering failure injection strategies. Our experimental evaluation validates the efficiency of our approach against the aforementioned security issues with a detection and recovery rate of over 96 %. KW - Cloud-Security KW - Cloud Audit KW - Security Metrics KW - Security Risk Assessment KW - Secure Configuration Y1 - 2018 SN - 978-1-5386-7659-2 U6 - https://doi.org/10.1109/NCA.2018.8548329 PB - IEEE CY - New York ER - TY - GEN A1 - Torkura, Kennedy A. A1 - Sukmana, Muhammad Ihsan Haikal A1 - Meinig, Michael A1 - Kayem, Anne V. D. M. A1 - Cheng, Feng A1 - Meinel, Christoph A1 - Graupner, Hendrik T1 - Securing cloud storage brokerage systems through threat models T2 - Proceedings IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA) N2 - Cloud storage brokerage is an abstraction aimed at providing value-added services. However, Cloud Service Brokers are challenged by several security issues including enlarged attack surfaces due to integration of disparate components and API interoperability issues. Therefore, appropriate security risk assessment methods are required to identify and evaluate these security issues, and examine the efficiency of countermeasures. A possible approach for satisfying these requirements is employment of threat modeling concepts, which have been successfully applied in traditional paradigms. In this work, we employ threat models including attack trees, attack graphs and Data Flow Diagrams against a Cloud Service Broker (CloudRAID) and analyze these security threats and risks. Furthermore, we propose an innovative technique for combining Common Vulnerability Scoring System (CVSS) and Common Configuration Scoring System (CCSS) base scores in probabilistic attack graphs to cater for configuration-based vulnerabilities which are typically leveraged for attacking cloud storage systems. This approach is necessary since existing schemes do not provide sufficient security metrics, which are imperatives for comprehensive risk assessments. We demonstrate the efficiency of our proposal by devising CCSS base scores for two common attacks against cloud storage: Cloud Storage Enumeration Attack and Cloud Storage Exploitation Attack. These metrics are then used in Attack Graph Metric-based risk assessment. Our experimental evaluation shows that our approach caters for the aforementioned gaps and provides efficient security hardening options. Therefore, our proposals can be employed to improve cloud security. KW - Cloud-Security KW - Threat Models KW - Security Metrics KW - Security Risk Assessment KW - Secure Configuration Y1 - 2018 SN - 978-1-5386-2195-0 U6 - https://doi.org/10.1109/AINA.2018.00114 SN - 1550-445X SP - 759 EP - 768 PB - IEEE CY - New York ER - TY - GEN A1 - Torkura, Kennedy A. A1 - Sukmana, Muhammad Ihsan Haikal A1 - Kayem, Anne V. D. M. A1 - Cheng, Feng A1 - Meinel, Christoph T1 - A cyber risk based moving target defense mechanism for microservice architectures T2 - IEEE Intl Conf on Parallel & Distributed Processing with Applications, Ubiquitous Computing & Communications, Big Data & Cloud Computing, Social Computing & Networking, Sustainable Computing & Communications (ISPA/IUCC/BDCloud/SocialCom/SustainCom) N2 - Microservice Architectures (MSA) structure applications as a collection of loosely coupled services that implement business capabilities. The key advantages of MSA include inherent support for continuous deployment of large complex applications, agility and enhanced productivity. However, studies indicate that most MSA are homogeneous, and introduce shared vulnerabilites, thus vulnerable to multi-step attacks, which are economics-of-scale incentives to attackers. In this paper, we address the issue of shared vulnerabilities in microservices with a novel solution based on the concept of Moving Target Defenses (MTD). Our mechanism works by performing risk analysis against microservices to detect and prioritize vulnerabilities. Thereafter, security risk-oriented software diversification is employed, guided by a defined diversification index. The diversification is performed at runtime, leveraging both model and template based automatic code generation techniques to automatically transform programming languages and container images of the microservices. Consequently, the microservices attack surfaces are altered thereby introducing uncertainty for attackers while reducing the attackability of the microservices. Our experiments demonstrate the efficiency of our solution, with an average success rate of over 70% attack surface randomization. KW - Security Risk Assessment KW - Security Metrics KW - Moving Target Defense KW - Microservices Security KW - Application Container Security Y1 - 2018 SN - 978-1-7281-1141-4 U6 - https://doi.org/10.1109/BDCloud.2018.00137 SN - 2158-9178 SP - 932 EP - 939 PB - Institute of Electrical and Electronics Engineers CY - Los Alamitos ER - TY - THES A1 - Torcato Mordido, Gonçalo Filipe T1 - Diversification, compression, and evaluation methods for generative adversarial networks N2 - Generative adversarial networks (GANs) have been broadly applied to a wide range of application domains since their proposal. In this thesis, we propose several methods that aim to tackle different existing problems in GANs. Particularly, even though GANs are generally able to generate high-quality samples, the diversity of the generated set is often sub-optimal. Moreover, the common increase of the number of models in the original GANs framework, as well as their architectural sizes, introduces additional costs. Additionally, even though challenging, the proper evaluation of a generated set is an important direction to ultimately improve the generation process in GANs. We start by introducing two diversification methods that extend the original GANs framework to multiple adversaries to stimulate sample diversity in a generated set. Then, we introduce a new post-training compression method based on Monte Carlo methods and importance sampling to quantize and prune the weights and activations of pre-trained neural networks without any additional training. The previous method may be used to reduce the memory and computational costs introduced by increasing the number of models in the original GANs framework. Moreover, we use a similar procedure to quantize and prune gradients during training, which also reduces the communication costs between different workers in a distributed training setting. We introduce several topology-based evaluation methods to assess data generation in different settings, namely image generation and language generation. Our methods retrieve both single-valued and double-valued metrics, which, given a real set, may be used to broadly assess a generated set or separately evaluate sample quality and sample diversity, respectively. Moreover, two of our metrics use locality-sensitive hashing to accurately assess the generated sets of highly compressed GANs. The analysis of the compression effects in GANs paves the way for their efficient employment in real-world applications. Given their general applicability, the methods proposed in this thesis may be extended beyond the context of GANs. Hence, they may be generally applied to enhance existing neural networks and, in particular, generative frameworks. N2 - Generative adversarial networks (GANs) wurden seit ihrer Einführung in einer Vielzahl von Anwendungsbereichen eingesetzt. In dieser Dissertation schlagen wir einige Verfahren vor, die darauf abzielen, verschiedene bestehende Probleme von GANs zu lösen. Insbesondere, fokussieren wir uns auf das Problem das GANs zwar qualitative hochwertige Samples generieren können, aber die Diversität ist oft sub-optimal. Darüber hinaus, stellt die allgemein übliche Zunahme der Anzahl der Modelle unter dem ursprünglichen GAN-Framework, als auch deren Modellgröße weitere Aufwendungskosten dar. Abschließend, ist die richtige Evaluierung einer generierten Menge, wenn auch herausfordernd, eine wichtige Forschungsrichtung, um letztendlich den Generierungsprozess von GANs zu verbessern. Wir beginnen mit der Einführung von zwei Diversifizierungsmethoden die das ursprüngliche GAN-Framework um mehrere Gegenspieler erweitern, um die Diversität zu erhöhen. Um den zusätzlichen Speicher- und Rechenaufwand zu reduzieren, führen wir dann eine neue Kompressionsmethode ein. Diese Methode basiert auf den Monte-Carlo-Methoden und Importance Sampling, für das Quantisieren und Pruning der Gewichte und Aktivierungen von schon trainierten neuronalen Netzwerken ohne zusätzliches Trainieren. Wir erweitern die erwähne Methode zusätzlich für das Quantisieren und Pruning von Gradienten während des Trainierens, was die Kommunikationskosten zwischen verschiedenen sogenannten „Workern“ in einer verteilten Trainingsumgebung reduziert. Bezüglich der Bewertung der generierten Samples, stellen wir mehrere typologie basierte Evaluationsmethoden vor, die sich auf Bild-und Text konzentrieren. Um verschiedene Anwendungsfälle zu erfassen, liefern unsere vorgestellten Methoden einwertige und doppelwertige Metriken. Diese können einerseits dazu genutzt werden, generierte Samples, oder die Qualität und Verteilung der Samples anhand einer Menge von echten Samples zu bewerten. Außerdem, verwenden zwei unserer vorgestellten Metriken so genanntes locality-sensitive Hashing, um die generierten Samples von stark komprimierten GANs genau zu bewerten. Die Analyse von Kompressionseffekten in GANs ebnet den Weg für ihren effizienten Einsatz für reale Anwendungen. Aufgrund der allgemeinen Anwendungsmöglichkeit von GANs, können die in dieser Arbeit vorgestellten Methoden auch über Kontext von GANs hinaus erweitert werden. Daher könnten sie allgemein auf existierende neuronale Netzwerke angewandt werden und insbesondere auf generative Frameworks. KW - deep learning KW - generative adversarial networks KW - erzeugende gegnerische Netzwerke KW - tiefes Lernen Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-535460 ER - TY - JOUR A1 - Topali, Paraskevi A1 - Chounta, Irene-Angelica A1 - Ortega-Arranz, Alejandro A1 - Villagrá-Sobrino, Sara L. A1 - Martínez-Monés, Alejandra T1 - CoFeeMOOC-v.2 BT - Designing Contingent Feedback for Massive Open Online Courses JF - EMOOCs 2021 N2 - Providing adequate support to MOOC participants is often a challenging task due to massiveness of the learners’ population and the asynchronous communication among peers and MOOC practitioners. This workshop aims at discussing common learners’ problems reported in the literature and reflect on designing adequate feedback interventions with the use of learning data. Our aim is three-fold: a) to pinpoint MOOC aspects that impact the planning of feedback, b) to explore the use of learning data in designing feedback strategies, and c) to propose design guidelines for developing and delivering scaffolding interventions for personalized feedback in MOOCs. To do so, we will carry out hands-on activities that aim to involve participants in interpreting learning data and using them to design adaptive feedback. This workshop appeals to researchers, practitioners and MOOC stakeholders who aim to providing contextualized scaffolding. We envision that this workshop will provide insights for bridging the gap between pedagogical theory and practice when it comes to feedback interventions in MOOCs. Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-517241 SN - 978-3-86956-512-5 VL - 2021 SP - 209 EP - 217 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Thomas, Max A1 - Staubitz, Thomas A1 - Meinel, Christoph ED - Meinel, Christoph ED - Schweiger, Stefanie ED - Staubitz, Thomas ED - Conrad, Robert ED - Alario Hoyos, Carlos ED - Ebner, Martin ED - Sancassani, Susanna ED - Żur, Agnieszka ED - Friedl, Christian ED - Halawa, Sherif ED - Gamage, Dilrukshi ED - Scott, Jeffrey ED - Kristine Jonson Carlon, May ED - Deville, Yves ED - Gaebel, Michael ED - Delgado Kloos, Carlos ED - von Schmieden, Karen T1 - Preparing MOOChub metadata for the future of online learning BT - optimizing for AI recommendation services JF - EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash? N2 - With the growing number of online learning resources, it becomes increasingly difficult and overwhelming to keep track of the latest developments and to find orientation in the plethora of offers. AI-driven services to recommend standalone learning resources or even complete learning paths are discussed as a possible solution for this challenge. To function properly, such services require a well-defined set of metadata provided by the learning resource. During the last few years, the so-called MOOChub metadata format has been established as a de-facto standard by a group of MOOC providers in German-speaking countries. This format, which is based on schema.org, already delivers a quite comprehensive set of metadata. So far, this set has been sufficient to list, display, sort, filter, and search for courses on several MOOC and open educational resources (OER) aggregators. AI recommendation services and further automated integration, beyond a plain listing, have special requirements, however. To optimize the format for proper support of such systems, several extensions and modifications have to be applied. We herein report on a set of suggested changes to prepare the format for this task. KW - Digitale Bildung KW - Kursdesign KW - MOOC KW - Micro Degree KW - Online-Lehre KW - Onlinekurs KW - Onlinekurs-Produktion KW - digital education KW - e-learning KW - micro degree KW - micro-credential KW - online course creation KW - online course design KW - online teaching Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-624830 SP - 329 EP - 338 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Thirouard, Maria A1 - de la Villèsbrunne, Marie A1 - Bernaert, Oliver ED - Meinel, Christoph ED - Schweiger, Stefanie ED - Staubitz, Thomas ED - Conrad, Robert ED - Alario Hoyos, Carlos ED - Ebner, Martin ED - Sancassani, Susanna ED - Żur, Agnieszka ED - Friedl, Christian ED - Halawa, Sherif ED - Gamage, Dilrukshi ED - Scott, Jeffrey ED - Kristine Jonson Carlon, May ED - Deville, Yves ED - Gaebel, Michael ED - Delgado Kloos, Carlos ED - von Schmieden, Karen T1 - From MOOC to “2M-POC” BT - an approach to transform a traditional MOOC to an efficient multi-modal learning path for companies JF - EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash? N2 - IFP School develops and produces MOOCs since 2014. After the COVID-19 crisis, the demand of our industrial and international partners to offer continuous training to their employees increased drastically in an energy transition and sustainable mobility environment that finds itself in constant and rapid evolution. Therefore, it is time for a new format of digital learning tools to efficiently and rapidly train an important number of employees. To address this new demand, in a more and more digital learning environment, we have completely changed our initial MOOC model to propose an innovative SPOC business model mixing synchronous and asynchronous modules. This paper describes the work that has been done to transform our MOOCs to a hybrid SPOC model. We changed the format itself from a standard MOOC model of several weeks to small modules of one week average more adapted to our client’s demand. We precisely engineered the exchanges between learners and the social aspect all along the SPOC duration. We propose a multimodal approach with a combination of asynchronous activities like online module, exercises, and synchronous activities like webinars with experts, and after-work sessions. Additionally, this new format increases the number of uses of the MOOC resources by our professors in our own master programs. With all these actions, we were able to reach a completion rate between 80 and 96% – total enrolled –, compared to the completion rate of 15 to 28% – total enrolled – as to be recorded in our original MOOC format. This is to be observed for small groups (50–100 learners) as SPOC but also for large groups (more than 2500 learners), as a Massive and Multimodal Private Online Course (“2M-POC”). Today a MOOC is not a simple assembly of videos, text, discussions forums and validation exercises but a complete multimodal learning path including social learning, personal followup, synchronous and asynchronous modules. We conclude that the original MOOC format is not at all suitable to propose efficient training to companies, and we must re-engineer the learning path to have a SPOC hybrid and multimodal training compatible with a cost-effective business model. KW - Digitale Bildung KW - Kursdesign KW - MOOC KW - Micro Degree KW - Online-Lehre KW - Onlinekurs KW - Onlinekurs-Produktion KW - digital education KW - e-learning KW - micro degree KW - micro-credential KW - online course creation KW - online course design KW - online teaching Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-624268 SP - 187 EP - 200 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Thienen, Julia von A1 - Weinstein, Theresa Julia A1 - Meinel, Christoph T1 - Creative metacognition in design thinking BT - exploring theories, educational practices, and their implications for measurement JF - Frontiers in psychology N2 - Design thinking is a well-established practical and educational approach to fostering high-level creativity and innovation, which has been refined since the 1950s with the participation of experts like Joy Paul Guilford and Abraham Maslow. Through real-world projects, trainees learn to optimize their creative outcomes by developing and practicing creative cognition and metacognition. This paper provides a holistic perspective on creativity, enabling the formulation of a comprehensive theoretical framework of creative metacognition. It focuses on the design thinking approach to creativity and explores the role of metacognition in four areas of creativity expertise: Products, Processes, People, and Places. The analysis includes task-outcome relationships (product metacognition), the monitoring of strategy effectiveness (process metacognition), an understanding of individual or group strengths and weaknesses (people metacognition), and an examination of the mutual impact between environments and creativity (place metacognition). It also reviews measures taken in design thinking education, including a distribution of cognition and metacognition, to support students in their development of creative mastery. On these grounds, we propose extended methods for measuring creative metacognition with the goal of enhancing comprehensive assessments of the phenomenon. Proposed methodological advancements include accuracy sub-scales, experimental tasks where examinees explore problem and solution spaces, combinations of naturalistic observations with capability testing, as well as physiological assessments as indirect measures of creative metacognition. KW - accuracy KW - creativity KW - design thinking KW - education KW - measurement KW - metacognition KW - innovation KW - framework Y1 - 2023 U6 - https://doi.org/10.3389/fpsyg.2023.1157001 SN - 1664-1078 VL - 14 PB - Frontiers Research Foundation CY - Lausanne ER - TY - JOUR A1 - Thienen, Julia von A1 - Clancey, William J. A1 - Corazza, Giovanni Emanuele A1 - Meinel, Christoph T1 - Theoretical foundations of design thinking creative thinking theories JF - Design Thinking Research: Making Distinctions: Collaboration versus Cooperation N2 - Design thinking is acknowledged as a thriving innovation practice plus something more, something in the line of a deep understanding of innovation processes. At the same time, quite how and why design thinking works-in scientific terms-appeared an open question at first. Over recent years, empirical research has achieved great progress in illuminating the principles that make design thinking successful. Lately, the community began to explore an additional approach. Rather than setting up novel studies, investigations into the history of design thinking hold the promise of adding systematically to our comprehension of basic principles. This chapter makes a start in revisiting design thinking history with the aim of explicating scientific understandings that inform design thinking practices today. It offers a summary of creative thinking theories that were brought to Stanford Engineering in the 1950s by John E. Arnold. Y1 - 2018 SN - 978-3-319-60967-6 SN - 978-3-319-60966-9 U6 - https://doi.org/10.1007/978-3-319-60967-6_2 SP - 13 EP - 40 PB - Springer CY - New York ER - TY - JOUR A1 - Theeraroungchaisri, Anuchai A1 - Thammetar, Thapanee A1 - Duangchinda, Vorasuang A1 - Khlaisang, Jintavee ED - Meinel, Christoph ED - Schweiger, Stefanie ED - Staubitz, Thomas ED - Conrad, Robert ED - Alario Hoyos, Carlos ED - Ebner, Martin ED - Sancassani, Susanna ED - Żur, Agnieszka ED - Friedl, Christian ED - Halawa, Sherif ED - Gamage, Dilrukshi ED - Scott, Jeffrey ED - Kristine Jonson Carlon, May ED - Deville, Yves ED - Gaebel, Michael ED - Delgado Kloos, Carlos ED - von Schmieden, Karen T1 - Thai MOOC academy BT - extending the platform towards a sandbox for the National Credit Bank System in Thailand JF - EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash? N2 - Thai MOOC Academy is a national digital learning platform that has been serving as a mechanism for promoting lifelong learning in Thailand since 2017. It has recently undergone significant improvements and upgrades, including the implementation of a credit bank system and a learner’s eportfolio system interconnected with the platform. Thai MOOC Academy is introducing a national credit bank system for accreditation and management, which allows for the transfer of expected learning outcomes and educational qualifications between formal education, non-formal education, and informal education. The credit bank system has five distinct features, including issuing forgery-prevented certificates, recording learning results, transferring external credits within the same wallet, accumulating learning results, and creating a QR code for verification purposes. The paper discusses the features and future potential of Thai MOOC Academy, as it is extended towards a sandbox for the national credit bank system in Thailand. KW - Digitale Bildung KW - Kursdesign KW - MOOC KW - Micro Degree KW - Online-Lehre KW - Onlinekurs KW - Onlinekurs-Produktion KW - digital education KW - e-learning KW - micro degree KW - micro-credential KW - online course creation KW - online course design KW - online teaching Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-624212 SP - 163 EP - 169 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - GEN A1 - Teusner, Ralf A1 - Matthies, Christoph A1 - Staubitz, Thomas T1 - What Stays in Mind? BT - Retention Rates in Programming MOOCs T2 - IEEE Frontiers in Education Conference (FIE) Y1 - 2018 SN - 978-1-5386-1174-6 U6 - https://doi.org/10.1109/FIE.2018.8658890 SN - 0190-5848 PB - IEEE CY - New York ER - TY - THES A1 - Teusner, Ralf T1 - Situational interventions and peer feedback in massive open online courses T1 - Situationsabhängige Interventionen und Peer-Feedback in Massive Open Online Courses BT - narrowing the gap between learners and instructors in online programming education N2 - Massive Open Online Courses (MOOCs) open up new opportunities to learn a wide variety of skills online and are thus well suited for individual education, especially where proffcient teachers are not available locally. At the same time, modern society is undergoing a digital transformation, requiring the training of large numbers of current and future employees. Abstract thinking, logical reasoning, and the need to formulate instructions for computers are becoming increasingly relevant. A holistic way to train these skills is to learn how to program. Programming, in addition to being a mental discipline, is also considered a craft, and practical training is required to achieve mastery. In order to effectively convey programming skills in MOOCs, practical exercises are incorporated into the course curriculum to offer students the necessary hands-on experience to reach an in-depth understanding of the programming concepts presented. Our preliminary analysis showed that while being an integral and rewarding part of courses, practical exercises bear the risk of overburdening students who are struggling with conceptual misunderstandings and unknown syntax. In this thesis, we develop, implement, and evaluate different interventions with the aim to improve the learning experience, sustainability, and success of online programming courses. Data from four programming MOOCs, with a total of over 60,000 participants, are employed to determine criteria for practical programming exercises best suited for a given audience. Based on over five million executions and scoring runs from students' task submissions, we deduce exercise difficulties, students' patterns in approaching the exercises, and potential flaws in exercise descriptions as well as preparatory videos. The primary issue in online learning is that students face a social gap caused by their isolated physical situation. Each individual student usually learns alone in front of a computer and suffers from the absence of a pre-determined time structure as provided in traditional school classes. Furthermore, online learning usually presses students into a one-size-fits-all curriculum, which presents the same content to all students, regardless of their individual needs and learning styles. Any means of a personalization of content or individual feedback regarding problems they encounter are mostly ruled out by the discrepancy between the number of learners and the number of instructors. This results in a high demand for self-motivation and determination of MOOC participants. Social distance exists between individual students as well as between students and course instructors. It decreases engagement and poses a threat to learning success. Within this research, we approach the identified issues within MOOCs and suggest scalable technical solutions, improving social interaction and balancing content difficulty. Our contributions include situational interventions, approaches for personalizing educational content as well as concepts for fostering collaborative problem-solving. With these approaches, we reduce counterproductive struggles and create a universal improvement for future programming MOOCs. We evaluate our approaches and methods in detail to improve programming courses for students as well as instructors and to advance the state of knowledge in online education. Data gathered from our experiments show that receiving peer feedback on one's programming problems improves overall course scores by up to 17%. Merely the act of phrasing a question about one's problem improved overall scores by about 14%. The rate of students reaching out for help was significantly improved by situational just-in-time interventions. Request for Comment interventions increased the share of students asking for help by up to 158%. Data from our four MOOCs further provide detailed insight into the learning behavior of students. We outline additional significant findings with regard to student behavior and demographic factors. Our approaches, the technical infrastructure, the numerous educational resources developed, and the data collected provide a solid foundation for future research. N2 - MOOCs (Massive Open Online Courses) ermöglichen es jedem Interessierten sich in verschiedenen Fachrichtungen online weiterzubilden. Sie fördern die persönliche individuelle Entwicklung und ermöglichen lebenslanges Lernen auch dort, wo geeignete Lehrer nicht verfügbar sind. Unsere Gesellschaft befindet sich derzeit in der sogenannten "digitalen Transformation". Von vielen Arbeitnehmern werden in diesem Zusammenhang zunehmend Fähigkeiten wie abstraktes Denken und logisches Schlussfolgern erwartet. Das Erlernen einer Programmiersprache ist eine geeignete Möglichkeit, diese Fähigkeiten zu erlangen. Obwohl Programmieren als geistige Disziplin angesehen wird, ist es zu einem gewissen Grad auch ein Handwerk, bei dem sich das individuelle Können insbesondere durch stetige praktische Anwendung entwickelt. Um Programmierkenntnisse effektiv in einem MOOC zu vermitteln, sollten daher praktische Aufgaben von vornherein in den Lehrstoff des Kurses integriert werden, um die vorgestellten Konzepte geeignet zu vertiefen und zu festigen. Neben den positiven Aspekten für die Lernenden weisen praktische Programmieraufgaben jedoch auch ein erhöhtes Frustpotential auf. Kryptische Fehlermeldungen und teils unbekannte Syntax überfordern insbesondere diejenigen Teilnehmer, welche zusätzlich mit konzeptionellen Missverständnissen zu kämpfen haben. Im Rahmen dieser Arbeit entwickeln und analysieren wir mehrere Interventionsmöglichkeiten um die Lernerfahrung und den Lernerfolg von Teilnehmern in Programmier-MOOCs zu verbessern. Daten von über 60.000 Teilnehmern aus vier Programmier-MOOCs bilden die Grundlage für eine Analyse von Kriterien für geeignete Programmieraufgaben für spezifische Teilnehmergruppen. Auf Basis von 5 Millionen Codeausführungen von Teilnehmern leiten wir Schwachstellen in Aufgaben und typische Herangehensweisen der Teilnehmer ab. Die Hauptschwierigkeit beim Lernen in einer virtuellen Umgebung ist die durch physische Isolation hervorgerufene soziale Entkopplung. Jeder Teilnehmer lernt alleine vor einem Bildschirm, ein gemeinsamer Stundenplan wie im klassischen Schulunterricht fehlt. Weiterhin präsentieren bestehende online Kurse den Teilnehmern in der Regel lediglich universell einsetzbare Lerninhalte, welche in keiner Weise auf die jeweiligen Bedürfnisse und Vorerfahrungen der individuellen Teilnehmer angepasst sind. Personalisierte Lerninhalte bzw. individuelles Feedback sind in MOOCs aufgrund der großen Anzahl an Teilnehmern und der nur kleinen Anzahl an Lehrenden oft nur schwer bzw. gar nicht zu realisieren. Daraus resultieren wiederum hohe Anforderungen an das individuelle Durchhaltevermögen und die Selbstmotivation der MOOC-Teilnehmer. Die soziale Entkopplung manifestiert sich sowohl zwischen den Teilnehmern untereinander als auch zwischen den Lehrenden und den Teilnehmern. Negative Folgen sind ein häufig verringertes Engagement und damit eine Gefährdung des Lernerfolgs. In dieser Arbeit schlagen wir als Gegenmaßnahme skalierbare technische Lösungen vor, um die soziale Interaktion zu verbessern und inhaltliche Schwierigkeiten zu überwinden. Unsere wissenschaftlichen Beiträge umfassen situationsabhängige Interventionen, Ansätze zur Personalisierung von Lerninhalten, sowie Konzepte und Anreize zur Verbesserung der Kollaboration der Teilnehmer untereinander. Mit diesen Maßnahmen schaffen wir es, kontraproduktive Blockaden beim Lernen zu lösen und stellen damit einen universell einsetzbaren Ansatz zur Verbesserung von zukünftigen Progammier-MOOCs bereit. Die aus unseren Experimenten gesammelten Daten zeigen, dass bei Programmierproblemen gewährtes Feedback von anderen Teilnehmern die Gesamtpunktzahl innerhalb des Teilnehmerfeldes durchschnittlich um bis zu 17% verbessert. Bereits das Formulieren des jeweiligen individuellen Problems verbesserte die Gesamtpunktzahl um etwa 14%. Durch situative Interventionen konnte weiterhin der Anteil der Teilnehmer, die nach Hilfe fragen, um bis zu 158% gesteigert werden. Die gesammelten Daten aus unseren vier MOOCs ermöglichen darüber hinaus detaillierte Einblicke in das Lernverhalten der Teilnehmer. Wir zeigen zusätzlich Erkenntnisse in Bezug auf das Verhalten der Teilnehmer und zu demografischen Faktoren auf. Die in dieser Arbeit beschriebenen Ansätze, die geschaffene technische Infrastruktur, das entworfene Lehrmaterial, sowie der umfangreiche gesammelte Datenbestand bilden darüber hinaus eine vielversprechende Grundlage für weitere zukünftige Forschung. KW - programming KW - MOOC KW - intervention KW - collaboration KW - peer feedback KW - Programmierung KW - MOOC KW - Interventionen KW - Kollaboration KW - Peer-feedback Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-507587 ER - TY - GEN A1 - Teichmann, Malte A1 - Ullrich, Andre A1 - Gronau, Norbert T1 - Subject-oriented learning BT - a new perspective for vocational training in learning factories T2 - Procedia Manufacturing N2 - The transformation to a digitized company changes not only the work but also social context for the employees and requires inter alia new knowledge and skills from them. Additionally, individual action problems arise. This contribution proposes the subject-oriented learning theory, in which the employees´ action problems are the starting point of training activities in learning factories. In this contribution, the subject-oriented learning theory is exemplified and respective advantages for vocational training in learning factories are pointed out both theoretically and practically. Thereby, especially the individual action problems of learners and the infrastructure are emphasized as starting point for learning processes and competence development. KW - Subject-oriented learning KW - action problems KW - vocational training KW - learning factories Y1 - 2019 U6 - https://doi.org/10.1016/j.promfg.2019.03.012 SN - 2351-9789 VL - 31 SP - 72 EP - 78 PB - Elsevier CY - Amsterdam ER -