@article{HolfelderMulanskySchleeetal.2021, author = {Holfelder, Marc and Mulansky, Lena and Schlee, Winfried and Baumeister, Harald and Schobel, Johannes and Greger, Helmut and Hoff, Andreas and Pryss, R{\"u}diger}, title = {Medical device regulation efforts for mHealth apps during the COVID-19 pandemic — an experience report of Corona Check and Corona Health}, series = {J — Multidisciplinary Scientific Journal}, volume = {4}, journal = {J — Multidisciplinary Scientific Journal}, number = {2}, issn = {2571-8800}, doi = {10.3390/j4020017}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-285434}, pages = {206 -- 222}, year = {2021}, abstract = {Within the healthcare environment, mobile health (mHealth) applications (apps) are becoming more and more important. The number of new mHealth apps has risen steadily in the last years. Especially the COVID-19 pandemic has led to an enormous amount of app releases. In most countries, mHealth applications have to be compliant with several regulatory aspects to be declared a "medical app". However, the latest applicable medical device regulation (MDR) does not provide more details on the requirements for mHealth applications. When developing a medical app, it is essential that all contributors in an interdisciplinary team — especially software engineers — are aware of the specific regulatory requirements beforehand. The development process, however, should not be stalled due to integration of the MDR. Therefore, a developing framework that includes these aspects is required to facilitate a reliable and quick development process. The paper at hand introduces the creation of such a framework on the basis of the Corona Health and Corona Check apps. The relevant regulatory guidelines are listed and summarized as a guidance for medical app developments during the pandemic and beyond. In particular, the important stages and challenges faced that emerged during the entire development process are highlighted.}, language = {en} } @unpublished{Nassourou2010, author = {Nassourou, Mohamadou}, title = {Markup overlap: Improving Fragmentation Method}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-49084}, year = {2010}, abstract = {Overlapping is a common word used to describe documents whose structural dimensions cannot be adequately represented using tree structure. For instance a quotation that starts in one verse and ends in another verse. The problem of overlapping hierarchies is a recurring one, which has been addressed by a variety of approaches. There are XML based solutions as well as Non-XML ones. The XML-based solutions are: multiple documents, empty elements, fragmentation, out-of-line markup, JITT and BUVH. And the Non-XML approaches comprise CONCUR/XCONCUR, MECS, LMNL ...etc. This paper presents shortly state-of-the-art in overlapping hierarchies, and introduces two variations on the TEI fragmentation markup that have several advantages.}, subject = {XML}, language = {en} } @techreport{RieglerWernerKayal2022, type = {Working Paper}, author = {Riegler, Clemens and Werner, Lennart and Kayal, Hakan}, title = {MAPLE: Marsian Autorotation Probe Lander Experiment}, doi = {10.25972/OPUS-28239}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-282390}, pages = {7}, year = {2022}, abstract = {The first step towards aerial planetary exploration has been made. Ingenuity shows extremely promising results, and new missions are already underway. Rotorcraft are capable of flight. This capability could be utilized to support the last stages of Entry, Descent, and Landing. Thus, mass and complexity could be scaled down. Autorotation is one method of descent. It describes unpowered descent and landing, typically performed by helicopters in case of an engine failure. MAPLE is suggested to test these procedures and understand autorotation on other planets. In this series of experiments, the Ingenuity helicopter is utilized. Ingenuity would autorotate a "mid-air-landing" before continuing with normal flight. Ultimately, the collected data shall help to understand autorotation on Mars and its utilization for interplanetary exploration.}, language = {en} } @phdthesis{Krenzer2023, author = {Krenzer, Adrian}, title = {Machine learning to support physicians in endoscopic examinations with a focus on automatic polyp detection in images and videos}, doi = {10.25972/OPUS-31911}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-319119}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2023}, abstract = {Deep learning enables enormous progress in many computer vision-related tasks. Artificial Intel- ligence (AI) steadily yields new state-of-the-art results in the field of detection and classification. Thereby AI performance equals or exceeds human performance. Those achievements impacted many domains, including medical applications. One particular field of medical applications is gastroenterology. In gastroenterology, machine learning algorithms are used to assist examiners during interventions. One of the most critical concerns for gastroenterologists is the development of Colorectal Cancer (CRC), which is one of the leading causes of cancer-related deaths worldwide. Detecting polyps in screening colonoscopies is the essential procedure to prevent CRC. Thereby, the gastroenterologist uses an endoscope to screen the whole colon to find polyps during a colonoscopy. Polyps are mucosal growths that can vary in severity. This thesis supports gastroenterologists in their examinations with automated detection and clas- sification systems for polyps. The main contribution is a real-time polyp detection system. This system is ready to be installed in any gastroenterology practice worldwide using open-source soft- ware. The system achieves state-of-the-art detection results and is currently evaluated in a clinical trial in four different centers in Germany. The thesis presents two additional key contributions: One is a polyp detection system with ex- tended vision tested in an animal trial. Polyps often hide behind folds or in uninvestigated areas. Therefore, the polyp detection system with extended vision uses an endoscope assisted by two additional cameras to see behind those folds. If a polyp is detected, the endoscopist receives a vi- sual signal. While the detection system handles the additional two camera inputs, the endoscopist focuses on the main camera as usual. The second one are two polyp classification models, one for the classification based on shape (Paris) and the other on surface and texture (NBI International Colorectal Endoscopic (NICE) classification). Both classifications help the endoscopist with the treatment of and the decisions about the detected polyp. The key algorithms of the thesis achieve state-of-the-art performance. Outstandingly, the polyp detection system tested on a highly demanding video data set shows an F1 score of 90.25 \% while working in real-time. The results exceed all real-time systems in the literature. Furthermore, the first preliminary results of the clinical trial of the polyp detection system suggest a high Adenoma Detection Rate (ADR). In the preliminary study, all polyps were detected by the polyp detection system, and the system achieved a high usability score of 96.3 (max 100). The Paris classification model achieved an F1 score of 89.35 \% which is state-of-the-art. The NICE classification model achieved an F1 score of 81.13 \%. Furthermore, a large data set for polyp detection and classification was created during this thesis. Therefore a fast and robust annotation system called Fast Colonoscopy Annotation Tool (FastCAT) was developed. The system simplifies the annotation process for gastroenterologists. Thereby the i gastroenterologists only annotate key parts of the endoscopic video. Afterward, those video parts are pre-labeled by a polyp detection AI to speed up the process. After the AI has pre-labeled the frames, non-experts correct and finish the annotation. This annotation process is fast and ensures high quality. FastCAT reduces the overall workload of the gastroenterologist on average by a factor of 20 compared to an open-source state-of-art annotation tool.}, subject = {Deep Learning}, language = {en} } @techreport{LohGeisslerHossfeld2022, type = {Working Paper}, author = {Loh, Frank and Geißler, Stefan and Hoßfeld, Tobias}, title = {LoRaWAN Network Planning in Smart Environments: Towards Reliability, Scalability, and Cost Reduction}, series = {W{\"u}rzburg Workshop on Next-Generation Communication Networks (WueWoWas'22)}, journal = {W{\"u}rzburg Workshop on Next-Generation Communication Networks (WueWoWas'22)}, doi = {10.25972/OPUS-28082}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-280829}, pages = {4}, year = {2022}, abstract = {The goal in this work is to present a guidance for LoRaWAN planning to improve overall reliability for message transmissions and scalability. At the end, the cost component is discussed. Therefore, a five step approach is presented that helps to plan a LoRaWAN deployment step by step: Based on the device locations, an initial gateway placement is suggested followed by in-depth frequency and channel access planning. After an initial planning phase, updates for channel access and the initial gateway planning is suggested that should also be done periodically during network operation. Since current gateway placement approaches are only studied with random channel access, there is a lot of potential in the cell planning phase. Furthermore, the performance of different channel access approaches is highly related on network load, and thus cell size and sensor density. Last, the influence of different cell planning ideas on expected costs are discussed.}, subject = {Datennetz}, language = {en} } @article{WienrichCarolusMarkusetal.2023, author = {Wienrich, Carolin and Carolus, Astrid and Markus, Andr{\´e} and Augustin, Yannik and Pfister, Jan and Hotho, Andreas}, title = {Long-term effects of perceived friendship with intelligent voice assistants on usage behavior, user experience, and social perceptions}, series = {Computers}, volume = {12}, journal = {Computers}, number = {4}, issn = {2073-431X}, doi = {10.3390/computers12040077}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-313552}, year = {2023}, abstract = {Social patterns and roles can develop when users talk to intelligent voice assistants (IVAs) daily. The current study investigates whether users assign different roles to devices and how this affects their usage behavior, user experience, and social perceptions. Since social roles take time to establish, we equipped 106 participants with Alexa or Google assistants and some smart home devices and observed their interactions for nine months. We analyzed diverse subjective (questionnaire) and objective data (interaction data). By combining social science and data science analyses, we identified two distinct clusters—users who assigned a friendship role to IVAs over time and users who did not. Interestingly, these clusters exhibited significant differences in their usage behavior, user experience, and social perceptions of the devices. For example, participants who assigned a role to IVAs attributed more friendship to them used them more frequently, reported more enjoyment during interactions, and perceived more empathy for IVAs. In addition, these users had distinct personal requirements, for example, they reported more loneliness. This study provides valuable insights into the role-specific effects and consequences of voice assistants. Recent developments in conversational language models such as ChatGPT suggest that the findings of this study could make an important contribution to the design of dialogic human-AI interactions.}, language = {en} } @article{KlemzRote2022, author = {Klemz, Boris and Rote, G{\"u}nter}, title = {Linear-Time Algorithms for Maximum-Weight Induced Matchings and Minimum Chain Covers in Convex Bipartite Graphs}, series = {Algorithmica}, volume = {84}, journal = {Algorithmica}, number = {4}, issn = {1432-0541}, doi = {10.1007/s00453-021-00904-w}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-267876}, pages = {1064-1080}, year = {2022}, abstract = {A bipartite graph G=(U,V,E) is convex if the vertices in V can be linearly ordered such that for each vertex u∈U, the neighbors of u are consecutive in the ordering of V. An induced matching H of G is a matching for which no edge of E connects endpoints of two different edges of H. We show that in a convex bipartite graph with n vertices and m weighted edges, an induced matching of maximum total weight can be computed in O(n+m) time. An unweighted convex bipartite graph has a representation of size O(n) that records for each vertex u∈U the first and last neighbor in the ordering of V. Given such a compact representation, we compute an induced matching of maximum cardinality in O(n) time. In convex bipartite graphs, maximum-cardinality induced matchings are dual to minimum chain covers. A chain cover is a covering of the edge set by chain subgraphs, that is, subgraphs that do not contain induced matchings of more than one edge. Given a compact representation, we compute a representation of a minimum chain cover in O(n) time. If no compact representation is given, the cover can be computed in O(n+m) time. All of our algorithms achieve optimal linear running time for the respective problem and model, and they improve and generalize the previous results in several ways: The best algorithms for the unweighted problem versions had a running time of O(n\(^{2}\)) (Brandst{\"a}dt et al. in Theor. Comput. Sci. 381(1-3):260-265, 2007. https://doi.org/10.1016/j.tcs.2007.04.006). The weighted case has not been considered before.}, language = {en} } @article{FischerHarteltPuppe2023, author = {Fischer, Norbert and Hartelt, Alexander and Puppe, Frank}, title = {Line-level layout recognition of historical documents with background knowledge}, series = {Algorithms}, volume = {16}, journal = {Algorithms}, number = {3}, issn = {1999-4893}, doi = {10.3390/a16030136}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-310938}, year = {2023}, abstract = {Digitization and transcription of historic documents offer new research opportunities for humanists and are the topics of many edition projects. However, manual work is still required for the main phases of layout recognition and the subsequent optical character recognition (OCR) of early printed documents. This paper describes and evaluates how deep learning approaches recognize text lines and can be extended to layout recognition using background knowledge. The evaluation was performed on five corpora of early prints from the 15th and 16th Centuries, representing a variety of layout features. While the main text with standard layouts could be recognized in the correct reading order with a precision and recall of up to 99.9\%, also complex layouts were recognized at a rate as high as 90\% by using background knowledge, the full potential of which was revealed if many pages of the same source were transcribed.}, language = {en} } @phdthesis{Somody2023, author = {Somody, Joseph Christian Campbell}, title = {Leveraging deep learning for identification and structural determination of novel protein complexes from \(in\) \(situ\) electron cryotomography of \(Mycoplasma\) \(pneumoniae\)}, doi = {10.25972/OPUS-31344}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-313447}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2023}, abstract = {The holy grail of structural biology is to study a protein in situ, and this goal has been fast approaching since the resolution revolution and the achievement of atomic resolution. A cell's interior is not a dilute environment, and proteins have evolved to fold and function as needed in that environment; as such, an investigation of a cellular component should ideally include the full complexity of the cellular environment. Imaging whole cells in three dimensions using electron cryotomography is the best method to accomplish this goal, but it comes with a limitation on sample thickness and produces noisy data unamenable to direct analysis. This thesis establishes a novel workflow to systematically analyse whole-cell electron cryotomography data in three dimensions and to find and identify instances of protein complexes in the data to set up a determination of their structure and identity for success. Mycoplasma pneumoniae is a very small parasitic bacterium with fewer than 700 protein-coding genes, is thin enough and small enough to be imaged in large quantities by electron cryotomography, and can grow directly on the grids used for imaging, making it ideal for exploratory studies in structural proteomics. As part of the workflow, a methodology for training deep-learning-based particle-picking models is established. As a proof of principle, a dataset of whole-cell Mycoplasma pneumoniae tomograms is used with this workflow to characterize a novel membrane-associated complex observed in the data. Ultimately, 25431 such particles are picked from 353 tomograms and refined to a density map with a resolution of 11 {\AA}. Making good use of orthogonal datasets to filter search space and verify results, structures were predicted for candidate proteins and checked for suitable fit in the density map. In the end, with this approach, nine proteins were found to be part of the complex, which appears to be associated with chaperone activity and interact with translocon machinery. Visual proteomics refers to the ultimate potential of in situ electron cryotomography: the comprehensive interpretation of tomograms. The workflow presented here is demonstrated to help in reaching that potential.}, subject = {Kryoelektronenmikroskopie}, language = {en} } @phdthesis{Dang2012, author = {Dang, Nghia Duc}, title = {Konzeption und Evaluation eines hybriden, skalierbaren Werkzeugs zur mechatronischen Systemdiagnose am Beispiel eines Diagnosesystems f{\"u}r freie Kfz-Werkst{\"a}tten}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-70774}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2012}, abstract = {Die Entwicklung eines wissensbasierten Systems, speziell eines Diagnosesystems, ist eine Teildisziplin der k{\"u}nstlichen Intelligenz und angewandten Informatik. Im Laufe der Forschung auf diesem Gebiet wurden verschiedene L{\"o}sungsans{\"a}tze mit unterschiedlichem Erfolg bei der Anwendung in der Kraftfahrzeugdiagnose entwickelt. Diagnosesysteme in Vertragswerkst{\"a}tten, das heißt in Fahrzeughersteller gebundenen Werkst{\"a}tten, wenden haupts{\"a}chlich die fallbasierte Diagnostik an. Zum einen h{\"a}lt sich hier die Fahrzeugvielfalt in Grenzen und zum anderen besteht eine Meldepflicht bei neuen, nicht im System vorhandenen F{\"a}llen. Die freien Werkst{\"a}tten verf{\"u}gen nicht {\"u}ber eine solche Datenbank. Somit ist der fallbasierte Ansatz schwer umsetzbar. In freien Werkst{\"a}tten - Fahrzeughersteller unabh{\"a}ngigen Werkst{\"a}tten - basiert die Fehlersuche haupts{\"a}chlich auf Fehlerb{\"a}umen. Wegen der wachsenden Fahrzeugkomplexit{\"a}t, welche wesentlich durch die stark zunehmende Anzahl der durch mechatronische Systeme realisierten Funktionen bedingt ist, und der steigenden Typenvielfalt ist die gef{\"u}hrte Fehlersuche in freien Werkst{\"a}tten nicht immer zielf{\"u}hrend. Um die Unterst{\"u}tzung des Personals von freien Werkst{\"a}tten bei der zuk{\"u}nftigen Fehlersuche zu gew{\"a}hrleisten, werden neue Generationen von herstellerunabh{\"a}ngigen Diagnosetools ben{\"o}tigt, die die Probleme der Variantenvielfalt und Komplexit{\"a}t l{\"o}sen. In der vorliegenden Arbeit wird ein L{\"o}sungsansatz vorgestellt, der einen qualitativen, modellbasierten Diagnoseansatz mit einem auf heuristischem Diagnosewissen basierenden Ansatz vereint. Neben der Grundlage zur Wissenserhebung werden in dieser Arbeit die theoretische Grundlage zur Beherrschung der Variantenvielfalt sowie die Tests f{\"u}r die erstellten Diagnosemodelle behandelt. Die Diagnose ist symptombasiert und die Inferenzmechanismen zur Verarbeitung des Diagnosewissens sind eine Kombination aus Propagierung der abweichenden physikalischen Gr{\"o}ßen im Modell und der Auswertung des heuristischen Wissens. Des Weiteren werden in dieser Arbeit verschiedene Aspekte der Realisierung der entwickelten theoretischen Grundlagen dargestellt, zum Beispiel: Systemarchitektur, Wissenserhebungsprozess, Ablauf des Diagnosevorgangs in den Werkst{\"a}tten. Die Evaluierung der entwickelten L{\"o}sung bei der Wissenserhebung in Form von Modellerstellungen und Modellierungsworkshops sowie Feldtests dient nicht nur zur Best{\"a}tigung des entwickelten Ansatzes, sondern auch zur Ideenfindung f{\"u}r die Integration der entwickelten Tools in die existierende IT-Infrastruktur.}, subject = {Diagnosesystem}, language = {de} }