@phdthesis{Azar2020, author = {Azar, Isabel}, title = {Konzeption und Evaluation eines webbasierten Patienteninformationsprogrammes zur {\"U}berpr{\"u}fung internistischer Verdachtsdiagnosen}, doi = {10.25972/OPUS-19964}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-199641}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2020}, abstract = {Das Thema dieser Dissertation lautet „Konzeption und Evaluation eines webbasierten Patienteninformationsprogrammes zur {\"U}berpr{\"u}fung internistischer Verdachtsdiagnosen". Zusammen mit dem Institut f{\"u}r Informatik wurde das wissensbasierte second-opinion-System SymptomCheck entwickelt. Das Programm dient zur {\"U}berpr{\"u}fung von Verdachtsdiagnosen. Es wurden Wissensbasen erstellt, in denen Symptome, Befunde und Untersuchungen nach einem Bewertungsschema beurteilt werden. Folgend wurde eine online erreichbare Startseite erstellt, auf der Nutzer vornehmlich internistische Verdachtsdiagnosen {\"u}berpr{\"u}fen k{\"o}nnen. Das Programm wurde in zwei Studien bez{\"u}glich seiner Sensitivit{\"a}t und Spezifit{\"a}t sowie der Benutzerfreundlichkeit getestet. In der ersten Studie wurden die Verdachtsdiagnosen ambulanter Patienten mit den {\"a}rztlich gestellten Diagnosen verglichen, eine zweite an die Allgemeinbev{\"o}lkerung gerichtete Onlinestudie galt vor allem der Bewertung der Benutzerfreundlichkeit. Soweit bekannt ist dies die erste Studie in der ein selbst entwickeltes Programm selbstst{\"a}ndig an echten Patienten getestet wurde.}, subject = {Entscheidungsunterst{\"u}tzungssystem}, language = {de} } @phdthesis{Roth2020, author = {Roth, Daniel}, title = {Intrapersonal, Interpersonal, and Hybrid Interactions in Virtual Reality}, doi = {10.25972/OPUS-18862}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-188627}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2020}, abstract = {Virtual reality and related media and communication technologies have a growing impact on professional application fields and our daily life. Virtual environments have the potential to change the way we perceive ourselves and how we interact with others. In comparison to other technologies, virtual reality allows for the convincing display of a virtual self-representation, an avatar, to oneself and also to others. This is referred to as user embodiment. Avatars can be of varying realism and abstraction in their appearance and in the behaviors they convey. Such userembodying interfaces, in turn, can impact the perception of the self as well as the perception of interactions. For researchers, designers, and developers it is of particular interest to understand these perceptual impacts, to apply them to therapy, assistive applications, social platforms, or games, for example. The present thesis investigates and relates these impacts with regard to three areas: intrapersonal effects, interpersonal effects, and effects of social augmentations provided by the simulation. With regard to intrapersonal effects, we specifically explore which simulation properties impact the illusion of owning and controlling a virtual body, as well as a perceived change in body schema. Our studies lead to the construction of an instrument to measure these dimensions and our results indicate that these dimensions are especially affected by the level of immersion, the simulation latency, as well as the level of personalization of the avatar. With regard to interpersonal effects we compare physical and user-embodied social interactions, as well as different degrees of freedom in the replication of nonverbal behavior. Our results suggest that functional levels of interaction are maintained, whereas aspects of presence can be affected by avatar-mediated interactions, and collaborative motor coordination can be disturbed by immersive simulations. Social interaction is composed of many unknown symbols and harmonic patterns that define our understanding and interpersonal rapport. For successful virtual social interactions, a mere replication of physical world behaviors to virtual environments may seem feasible. However, the potential of mediated social interactions goes beyond this mere replication. In a third vein of research, we propose and evaluate alternative concepts on how computers can be used to actively engage in mediating social interactions, namely hybrid avatar-agent technologies. Specifically, we investigated the possibilities to augment social behaviors by modifying and transforming user input according to social phenomena and behavior, such as nonverbal mimicry, directed gaze, joint attention, and grouping. Based on our results we argue that such technologies could be beneficial for computer-mediated social interactions such as to compensate for lacking sensory input and disturbances in data transmission or to increase aspects of social presence by visual substitution or amplification of social behaviors. Based on related work and presented findings, the present thesis proposes the perspective of considering computers as social mediators. Concluding from prototypes and empirical studies, the potential of technology to be an active mediator of social perception with regard to the perception of the self, as well as the perception of social interactions may benefit our society by enabling further methods for diagnosis, treatment, and training, as well as the inclusion of individuals with social disorders. To this regard, we discuss implications for our society and ethical aspects. This thesis extends previous empirical work and further presents novel instruments, concepts, and implications to open up new perspectives for the development of virtual reality, mixed reality, and augmented reality applications.}, subject = {Virtuelle Realit{\"a}t}, language = {en} } @phdthesis{Wick2020, author = {Wick, Christoph}, title = {Optical Medieval Music Recognition}, doi = {10.25972/OPUS-21434}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-214348}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2020}, abstract = {In recent years, great progress has been made in the area of Artificial Intelligence (AI) due to the possibilities of Deep Learning which steadily yielded new state-of-the-art results especially in many image recognition tasks. Currently, in some areas, human performance is achieved or already exceeded. This great development already had an impact on the area of Optical Music Recognition (OMR) as several novel methods relying on Deep Learning succeeded in specific tasks. Musicologists are interested in large-scale musical analysis and in publishing digital transcriptions in a collection enabling to develop tools for searching and data retrieving. The application of OMR promises to simplify and thus speed-up the transcription process by either providing fully-automatic or semi-automatic approaches. This thesis focuses on the automatic transcription of Medieval music with a focus on square notation which poses a challenging task due to complex layouts, highly varying handwritten notations, and degradation. However, since handwritten music notations are quite complex to read, even for an experienced musicologist, it is to be expected that even with new techniques of OMR manual corrections are required to obtain the transcriptions. This thesis presents several new approaches and open source software solutions for layout analysis and Automatic Text Recognition (ATR) for early documents and for OMR of Medieval manuscripts providing state-of-the-art technology. Fully Convolutional Networks (FCN) are applied for the segmentation of historical manuscripts and early printed books, to detect staff lines, and to recognize neume notations. The ATR engine Calamari is presented which allows for ATR of early prints and also the recognition of lyrics. Configurable CNN/LSTM-network architectures which are trained with the segmentation-free CTC-loss are applied to the sequential recognition of text but also monophonic music. Finally, a syllable-to-neume assignment algorithm is presented which represents the final step to obtain a complete transcription of the music. The evaluations show that the performances of any algorithm is highly depending on the material at hand and the number of training instances. The presented staff line detection correctly identifies staff lines and staves with an \$F_1\$-score of above \$99.5\\%\$. The symbol recognition yields a diplomatic Symbol Accuracy Rate (dSAR) of above \$90\\%\$ by counting the number of correct predictions in the symbols sequence normalized by its length. The ATR of lyrics achieved a Character Error Rate (CAR) (equivalently the number of correct predictions normalized by the sentence length) of above \$93\\%\$ trained on 771 lyric lines of Medieval manuscripts and of 99.89\\% when training on around 3.5 million lines of contemporary printed fonts. The assignment of syllables and their corresponding neumes reached \$F_1\$-scores of up to \$99.2\\%\$. A direct comparison to previously published performances is difficult due to different materials and metrics. However, estimations show that the reported values of this thesis exceed the state-of-the-art in the area of square notation. A further goal of this thesis is to enable musicologists without technical background to apply the developed algorithms in a complete workflow by providing a user-friendly and comfortable Graphical User Interface (GUI) encapsulating the technical details. For this purpose, this thesis presents the web-application OMMR4all. Its fully-functional workflow includes the proposed state-of-the-art machine-learning algorithms and optionally allows for a manual intervention at any stage to correct the output preventing error propagation. To simplify the manual (post-) correction, OMMR4all provides an overlay-editor that superimposes the annotations with a scan of the original manuscripts so that errors can easily be spotted. The workflow is designed to be iteratively improvable by training better models as soon as new Ground Truth (GT) is available.}, subject = {Neumenschrift}, language = {en} } @phdthesis{SchauerMarinRodrigues2020, author = {Schauer Marin Rodrigues, Johannes}, title = {Detecting Changes and Finding Collisions in 3D Point Clouds : Data Structures and Algorithms for Post-Processing Large Datasets}, isbn = {978-3-945459-32-4}, doi = {10.25972/OPUS-21428}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-214285}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2020}, abstract = {Affordable prices for 3D laser range finders and mature software solutions for registering multiple point clouds in a common coordinate system paved the way for new areas of application for 3D point clouds. Nowadays we see 3D laser scanners being used not only by digital surveying experts but also by law enforcement officials, construction workers or archaeologists. Whether the purpose is digitizing factory production lines, preserving historic sites as digital heritage or recording environments for gaming or virtual reality applications -- it is hard to imagine a scenario in which the final point cloud must also contain the points of "moving" objects like factory workers, pedestrians, cars or flocks of birds. For most post-processing tasks, moving objects are undesirable not least because moving objects will appear in scans multiple times or are distorted due to their motion relative to the scanner rotation. The main contributions of this work are two postprocessing steps for already registered 3D point clouds. The first method is a new change detection approach based on a voxel grid which allows partitioning the input points into static and dynamic points using explicit change detection and subsequently remove the latter for a "cleaned" point cloud. The second method uses this cleaned point cloud as input for detecting collisions between points of the environment point cloud and a point cloud of a model that is moved through the scene. Our approach on explicit change detection is compared to the state of the art using multiple datasets including the popular KITTI dataset. We show how our solution achieves similar or better F1-scores than an existing solution while at the same time being faster. To detect collisions we do not produce a mesh but approximate the raw point cloud data by spheres or cylindrical volumes. We show how our data structures allow efficient nearest neighbor queries that make our CPU-only approach comparable to a massively-parallel algorithm running on a GPU. The utilized algorithms and data structures are discussed in detail. All our software is freely available for download under the terms of the GNU General Public license. Most of the datasets used in this thesis are freely available as well. We provide shell scripts that allow one to directly reproduce the quantitative results shown in this thesis for easy verification of our findings.}, subject = {Punktwolke}, language = {en} } @article{KrupitzerTemizerPrantletal.2020, author = {Krupitzer, Christian and Temizer, Timur and Prantl, Thomas and Raibulet, Claudia}, title = {An Overview of Design Patterns for Self-Adaptive Systems in the Context of the Internet of Things}, series = {IEEE Access}, volume = {8}, journal = {IEEE Access}, doi = {10.1109/ACCESS.2020.3031189}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-229984}, pages = {187384-187399}, year = {2020}, abstract = {The Internet of Things (IoT) requires the integration of all available, highly specialized, and heterogeneous devices, ranging from embedded sensor nodes to servers in the cloud. The self-adaptive research domain provides adaptive capabilities that can support the integration in IoT systems. However, developing such systems is a challenging, error-prone, and time-consuming task. In this context, design patterns propose already used and optimized solutions to specific problems in various contexts. Applying design patterns might help to reuse existing knowledge about similar development issues. However, so far, there is a lack of taxonomies on design patterns for self-adaptive systems. To tackle this issue, in this paper, we provide a taxonomy on design patterns for self-adaptive systems that can be transferred to support adaptivity in IoT systems. Besides describing the taxonomy and the design patterns, we discuss their applicability in an Industrial IoT case study.}, language = {en} } @article{DuekingHolmbergKunzetal.2020, author = {D{\"u}king, Peter and Holmberg, Hans‑Christer and Kunz, Philipp and Leppich, Robert and Sperlich, Billy}, title = {Intra-individual physiological response of recreational runners to different training mesocycles: a randomized cross-over study}, series = {European Journal of Applied Physiology}, volume = {120}, journal = {European Journal of Applied Physiology}, issn = {1439-6319}, doi = {10.1007/s00421-020-04477-4}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-235022}, pages = {2705-2713}, year = {2020}, abstract = {Purpose Pronounced differences in individual physiological adaptation may occur following various training mesocycles in runners. Here we aimed to assess the individual changes in performance and physiological adaptation of recreational runners performing mesocycles with different intensity, duration and frequency. Methods Employing a randomized cross-over design, the intra-individual physiological responses [i.e., peak (\(\dot{VO}_{2peak}\)) and submaximal (\(\dot{VO}_{2submax}\)) oxygen uptake, velocity at lactate thresholds (V\(_2\), V\(_4\))] and performance (time-to-exhaustion (TTE)) of 13 recreational runners who performed three 3-week sessions of high-intensity interval training (HIIT), high-volume low-intensity training (HVLIT) or more but shorter sessions of HVLIT (high-frequency training; HFT) were assessed. Results \(\dot{VO}_{2submax}\), V\(_2\), V\(_4\) and TTE were not altered by HIIT, HVLIT or HFT (p > 0.05). \(\dot{VO}_{2peak}\) improved to the same extent following HVLIT (p = 0.045) and HFT (p = 0.02). The number of moderately negative responders was higher following HIIT (15.4\%); and HFT (15.4\%) than HVLIT (7.6\%). The number of very positive responders was higher following HVLIT (38.5\%) than HFT (23\%) or HIIT (7.7\%). 46\% of the runners responded positively to two mesocycles, while 23\% did not respond to any. Conclusion On a group level, none of the interventions altered \(\dot{VO}_{2submax}\), V\(_2\), V\(_4\) or TTE, while HVLIT and HFT improved \(\dot{VO}_{2peak}\). The mean adaptation index indicated similar numbers of positive, negative and non-responders to HIIT, HVLIT and HFT, but more very positive responders to HVLIT than HFT or HIIT. 46\% responded positively to two mesocycles, while 23\% did not respond to any. These findings indicate that the magnitude of responses to HIIT, HVLIT and HFT is highly individual and no pattern was apparent.}, language = {en} } @article{FreyGassenmaierHofmannetal.2020, author = {Frey, Anna and Gassenmaier, Tobias and Hofmann, Ulrich and Schmitt, Dominik and Fette, Georg and Marx, Almuth and Heterich, Sabine and Boivin-Jahns, Val{\´e}rie and Ertl, Georg and Bley, Thorsten and Frantz, Stefan and Jahns, Roland and St{\"o}rk, Stefan}, title = {Coagulation factor XIII activity predicts left ventricular remodelling after acute myocardial infarction}, series = {ESC Heart Failure}, volume = {7}, journal = {ESC Heart Failure}, number = {5}, doi = {10.1002/ehf2.12774}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-236013}, pages = {2354-2364}, year = {2020}, abstract = {Aims Acute myocardial infarction (MI) is the major cause of chronic heart failure. The activity of blood coagulation factor XIII (FXIIIa) plays an important role in rodents as a healing factor after MI, whereas its role in healing and remodelling processes in humans remains unclear. We prospectively evaluated the relevance of FXIIIa after acute MI as a potential early prognostic marker for adequate healing. Methods and results This monocentric prospective cohort study investigated cardiac remodelling in patients with ST-elevation MI and followed them up for 1 year. Serum FXIIIa was serially assessed during the first 9 days after MI and after 2, 6, and 12 months. Cardiac magnetic resonance imaging was performed within 4 days after MI (Scan 1), after 7 to 9 days (Scan 2), and after 12 months (Scan 3). The FXIII valine-to-leucine (V34L) single-nucleotide polymorphism rs5985 was genotyped. One hundred forty-six patients were investigated (mean age 58 ± 11 years, 13\% women). Median FXIIIa was 118 \% (quartiles, 102-132\%) and dropped to a trough on the second day after MI: 109\%(98-109\%; P < 0.001). FXIIIa recovered slowly over time, reaching the baseline level after 2 to 6 months and surpassed baseline levels only after 12 months: 124 \% (110-142\%). The development of FXIIIa after MI was independent of the genotype. FXIIIa on Day 2 was strongly and inversely associated with the relative size of MI in Scan 1 (Spearman's ρ = -0.31; P = 0.01) and Scan 3 (ρ = -0.39; P < 0.01) and positively associated with left ventricular ejection fraction: ρ = 0.32 (P < 0.01) and ρ = 0.24 (P = 0.04), respectively. Conclusions FXIII activity after MI is highly dynamic, exhibiting a significant decline in the early healing period, with reconstitution 6 months later. Depressed FXIIIa early after MI predicted a greater size of MI and lower left ventricular ejection fraction after 1 year. The clinical relevance of these findings awaits to be tested in a randomized trial.}, language = {en} } @masterthesis{Hofmann2020, type = {Bachelor Thesis}, author = {Hofmann, Jan}, title = {Deep Reinforcement Learning for Configuration of Time-Sensitive-Networking}, doi = {10.25972/OPUS-21595}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-215953}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2020}, abstract = {Reliable, deterministic real-time communication is fundamental to most industrial systems today. In many other domains Ethernet has become the most common platform for communication networks, but has been unsuitable to satisfy the requirements of industrial networks for a long time. This has changed with the introduction of Time-Sensitive-Networking (TSN), a set of standards utilizing Ethernet to implement deterministic real-time networks. This makes Ethernet a viable alternative to the expensive fieldbus systems commonly used in industrial environments. However, TSN is not a silver bullet. Industrial networks are a complex and highly dynamic environment and the configuration of TSN, especially with respect to latency, is a challenging but crucial task. Various approaches have been pursued for the configuration of TSN in dynamic industrial environments. Optimization techniques like Linear Programming (LP) are able to determine an optimal configuration for a given network, but the time consumption exponentially increases with the complexity of the environment. Machine Learning (ML) has become widely popular in the last years and is able to approximate a near-optimal TSN configuration for networks of different complexity. Yet, ML models are usually trained in a supervised manner which requires large amounts of data that have to be generated for the specific environment. Therefore, supervised methods are not scalable and do not adapt to changing dynamics of the network environment. To address these issues, this work proposes a Deep Reinforcement Learning (DRL) approach to the configuration of TSN in industrial networks. DRL combines two different disciplines, Deep Learning (DL) and Reinforcement Learning (RL), and has gained considerable traction in the last years due to breakthroughs in various domains. RL is supposed to autonomously learn a challenging task like the configuration of TSN without requiring any training data. The addition of DL allows to apply well-studied RL methods to a complex environment such as dynamic industrial networks. There are two major contributions made in this work. In the first step, an interactive environment is proposed which allows for the simulation and configuration of industrial networks using basic TSN mechanisms. The environment provides an interface that allows to apply various DRL methods to the problem of TSN configuration. The second contribution of this work is an in-depth study on the application of two fundamentally different DRL methods to the proposed environment. Both methods are evaluated on networks of different complexity and the results are compared to the ground truth and to the results of two supervised ML approaches. Ultimately, this work investigates if DRL can adapt to changing dynamics of the environment in a more scalable manner than supervised methods.}, subject = {Reinforcement Learning}, language = {en} } @article{SchloerRingHotho2020, author = {Schl{\"o}r, Daniel and Ring, Markus and Hotho, Andreas}, title = {iNALU: Improved Neural Arithmetic Logic Unit}, series = {Frontiers in Artificial Intelligence}, volume = {3}, journal = {Frontiers in Artificial Intelligence}, issn = {2624-8212}, doi = {10.3389/frai.2020.00071}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-212301}, year = {2020}, abstract = {Neural networks have to capture mathematical relationships in order to learn various tasks. They approximate these relations implicitly and therefore often do not generalize well. The recently proposed Neural Arithmetic Logic Unit (NALU) is a novel neural architecture which is able to explicitly represent the mathematical relationships by the units of the network to learn operations such as summation, subtraction or multiplication. Although NALUs have been shown to perform well on various downstream tasks, an in-depth analysis reveals practical shortcomings by design, such as the inability to multiply or divide negative input values or training stability issues for deeper networks. We address these issues and propose an improved model architecture. We evaluate our model empirically in various settings from learning basic arithmetic operations to more complex functions. Our experiments indicate that our model solves stability issues and outperforms the original NALU model in means of arithmetic precision and convergence.}, language = {en} } @article{LiGuanGaoetal.2020, author = {Li, Ningbo and Guan, Lianwu and Gao, Yanbin and Du, Shitong and Wu, Menghao and Guang, Xingxing and Cong, Xiaodan}, title = {Indoor and outdoor low-cost seamless integrated navigation system based on the integration of INS/GNSS/LIDAR system}, series = {Remote Sensing}, volume = {12}, journal = {Remote Sensing}, number = {19}, issn = {2072-4292}, doi = {10.3390/rs12193271}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-216229}, year = {2020}, abstract = {Global Navigation Satellite System (GNSS) provides accurate positioning data for vehicular navigation in open outdoor environment. In an indoor environment, Light Detection and Ranging (LIDAR) Simultaneous Localization and Mapping (SLAM) establishes a two-dimensional map and provides positioning data. However, LIDAR can only provide relative positioning data and it cannot directly provide the latitude and longitude of the current position. As a consequence, GNSS/Inertial Navigation System (INS) integrated navigation could be employed in outdoors, while the indoors part makes use of INS/LIDAR integrated navigation and the corresponding switching navigation will make the indoor and outdoor positioning consistent. In addition, when the vehicle enters the garage, the GNSS signal will be blurred for a while and then disappeared. Ambiguous GNSS satellite signals will lead to the continuous distortion or overall drift of the positioning trajectory in the indoor condition. Therefore, an INS/LIDAR seamless integrated navigation algorithm and a switching algorithm based on vehicle navigation system are designed. According to the experimental data, the positioning accuracy of the INS/LIDAR navigation algorithm in the simulated environmental experiment is 50\% higher than that of the Dead Reckoning (DR) algorithm. Besides, the switching algorithm developed based on the INS/LIDAR integrated navigation algorithm can achieve 80\% success rate in navigation mode switching.}, language = {en} }