@article{WickHarteltPuppe2019, author = {Wick, Christoph and Hartelt, Alexander and Puppe, Frank}, title = {Staff, symbol and melody detection of Medieval manuscripts written in square notation using deep Fully Convolutional Networks}, series = {Applied Sciences}, volume = {9}, journal = {Applied Sciences}, number = {13}, issn = {2076-3417}, doi = {10.3390/app9132646}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-197248}, year = {2019}, abstract = {Even today, the automatic digitisation of scanned documents in general, but especially the automatic optical music recognition (OMR) of historical manuscripts, still remains an enormous challenge, since both handwritten musical symbols and text have to be identified. This paper focuses on the Medieval so-called square notation developed in the 11th-12th century, which is already composed of staff lines, staves, clefs, accidentals, and neumes that are roughly spoken connected single notes. The aim is to develop an algorithm that captures both the neumes, and in particular its melody, which can be used to reconstruct the original writing. Our pipeline is similar to the standard OMR approach and comprises a novel staff line and symbol detection algorithm based on deep Fully Convolutional Networks (FCN), which perform pixel-based predictions for either staff lines or symbols and their respective types. Then, the staff line detection combines the extracted lines to staves and yields an F\(_1\) -score of over 99\% for both detecting lines and complete staves. For the music symbol detection, we choose a novel approach that skips the step to identify neumes and instead directly predicts note components (NCs) and their respective affiliation to a neume. Furthermore, the algorithm detects clefs and accidentals. Our algorithm predicts the symbol sequence of a staff with a diplomatic symbol accuracy rate (dSAR) of about 87\%, which includes symbol type and location. If only the NCs without their respective connection to a neume, all clefs and accidentals are of interest, the algorithm reaches an harmonic symbol accuracy rate (hSAR) of approximately 90\%. In general, the algorithm recognises a symbol in the manuscript with an F\(_1\) -score of over 96\%.}, language = {en} } @article{DjebkoPuppeKayal2019, author = {Djebko, Kirill and Puppe, Frank and Kayal, Hakan}, title = {Model-based fault detection and diagnosis for spacecraft with an application for the SONATE triple cube nano-satellite}, series = {Aerospace}, volume = {6}, journal = {Aerospace}, number = {10}, issn = {2226-4310}, doi = {10.3390/aerospace6100105}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-198836}, pages = {105}, year = {2019}, abstract = {The correct behavior of spacecraft components is the foundation of unhindered mission operation. However, no technical system is free of wear and degradation. A malfunction of one single component might significantly alter the behavior of the whole spacecraft and may even lead to a complete mission failure. Therefore, abnormal component behavior must be detected early in order to be able to perform counter measures. A dedicated fault detection system can be employed, as opposed to classical health monitoring, performed by human operators, to decrease the response time to a malfunction. In this paper, we present a generic model-based diagnosis system, which detects faults by analyzing the spacecraft's housekeeping data. The observed behavior of the spacecraft components, given by the housekeeping data is compared to their expected behavior, obtained through simulation. Each discrepancy between the observed and the expected behavior of a component generates a so-called symptom. Given the symptoms, the diagnoses are derived by computing sets of components whose malfunction might cause the observed discrepancies. We demonstrate the applicability of the diagnosis system by using modified housekeeping data of the qualification model of an actual spacecraft and outline the advantages and drawbacks of our approach.}, language = {en} } @article{OberdoerferLatoschik2019, author = {Oberd{\"o}rfer, Sebastian and Latoschik, Marc Erich}, title = {Knowledge encoding in game mechanics: transfer-oriented knowledge learning in desktop-3D and VR}, series = {International Journal of Computer Games Technology}, volume = {2019}, journal = {International Journal of Computer Games Technology}, doi = {10.1155/2019/7626349}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-201159}, pages = {7626349}, year = {2019}, abstract = {Affine Transformations (ATs) are a complex and abstract learning content. Encoding the AT knowledge in Game Mechanics (GMs) achieves a repetitive knowledge application and audiovisual demonstration. Playing a serious game providing these GMs leads to motivating and effective knowledge learning. Using immersive Virtual Reality (VR) has the potential to even further increase the serious game's learning outcome and learning quality. This paper compares the effectiveness and efficiency of desktop-3D and VR in respect to the achieved learning outcome. Also, the present study analyzes the effectiveness of an enhanced audiovisual knowledge encoding and the provision of a debriefing system. The results validate the effectiveness of the knowledge encoding in GMs to achieve knowledge learning. The study also indicates that VR is beneficial for the overall learning quality and that an enhanced audiovisual encoding has only a limited effect on the learning outcome.}, language = {en} } @misc{FunkenTscherner2019, author = {Funken, Matthias and Tscherner, Michael}, title = {Jahresbericht 2018 des Rechenzentrums der Universit{\"a}t W{\"u}rzburg}, edition = {1. Auflage}, organization = {Rechenzentrum (Universit{\"a}t W{\"u}rzburg)}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-188265}, pages = {76}, year = {2019}, abstract = {Eine {\"U}bersicht {\"u}ber die Aktivit{\"a}ten des Rechenzentrums im Jahr 2018.}, subject = {Julius-Maximilians-Universit{\"a}t W{\"u}rzburg}, language = {de} } @article{LopezArreguinMontenegro2019, author = {Lopez-Arreguin, A. J. R. and Montenegro, S.}, title = {Improving engineering models of terramechanics for planetary exploration}, series = {Results in Engineering}, volume = {3}, journal = {Results in Engineering}, doi = {10.1016/j.rineng.2019.100027}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-202490}, pages = {100027}, year = {2019}, abstract = {This short letter proposes more consolidated explicit solutions for the forces and torques acting on typical rover wheels, that can be used as a method to determine their average mobility characteristics in planetary soils. The closed loop solutions stand in one of the verified methods, but at difference of the previous, observables are decoupled requiring a less amount of physical parameters to measure. As a result, we show that with knowledge of terrain properties, wheel driving performance rely in a single observable only. Because of their generality, the formulated equations established here can have further implications in autonomy and control of rovers or planetary soil characterization.}, language = {en} } @phdthesis{Niebler2019, author = {Niebler, Thomas}, title = {Extracting and Learning Semantics from Social Web Data}, doi = {10.25972/OPUS-17866}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-178666}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2019}, abstract = {Making machines understand natural language is a dream of mankind that existed since a very long time. Early attempts at programming machines to converse with humans in a supposedly intelligent way with humans relied on phrase lists and simple keyword matching. However, such approaches cannot provide semantically adequate answers, as they do not consider the specific meaning of the conversation. Thus, if we want to enable machines to actually understand language, we need to be able to access semantically relevant background knowledge. For this, it is possible to query so-called ontologies, which are large networks containing knowledge about real-world entities and their semantic relations. However, creating such ontologies is a tedious task, as often extensive expert knowledge is required. Thus, we need to find ways to automatically construct and update ontologies that fit human intuition of semantics and semantic relations. More specifically, we need to determine semantic entities and find relations between them. While this is usually done on large corpora of unstructured text, previous work has shown that we can at least facilitate the first issue of extracting entities by considering special data such as tagging data or human navigational paths. Here, we do not need to detect the actual semantic entities, as they are already provided because of the way those data are collected. Thus we can mainly focus on the problem of assessing the degree of semantic relatedness between tags or web pages. However, there exist several issues which need to be overcome, if we want to approximate human intuition of semantic relatedness. For this, it is necessary to represent words and concepts in a way that allows easy and highly precise semantic characterization. This also largely depends on the quality of data from which these representations are constructed. In this thesis, we extract semantic information from both tagging data created by users of social tagging systems and human navigation data in different semantic-driven social web systems. Our main goal is to construct high quality and robust vector representations of words which can the be used to measure the relatedness of semantic concepts. First, we show that navigation in the social media systems Wikipedia and BibSonomy is driven by a semantic component. After this, we discuss and extend methods to model the semantic information in tagging data as low-dimensional vectors. Furthermore, we show that tagging pragmatics influences different facets of tagging semantics. We then investigate the usefulness of human navigational paths in several different settings on Wikipedia and BibSonomy for measuring semantic relatedness. Finally, we propose a metric-learning based algorithm in adapt pre-trained word embeddings to datasets containing human judgment of semantic relatedness. This work contributes to the field of studying semantic relatedness between words by proposing methods to extract semantic relatedness from web navigation, learn highquality and low-dimensional word representations from tagging data, and to learn semantic relatedness from any kind of vector representation by exploiting human feedback. Applications first and foremest lie in ontology learning for the Semantic Web, but also semantic search or query expansion.}, subject = {Semantik}, language = {en} } @article{LodaKrebsDanhofetal.2019, author = {Loda, Sophia and Krebs, Jonathan and Danhof, Sophia and Schreder, Martin and Solimando, Antonio G. and Strifler, Susanne and Rasche, Leo and Kort{\"u}m, Martin and Kerscher, Alexander and Knop, Stefan and Puppe, Frank and Einsele, Hermann and Bittrich, Max}, title = {Exploration of artificial intelligence use with ARIES in multiple myeloma research}, series = {Journal of Clinical Medicine}, volume = {8}, journal = {Journal of Clinical Medicine}, number = {7}, issn = {2077-0383}, doi = {10.3390/jcm8070999}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-197231}, pages = {999}, year = {2019}, abstract = {Background: Natural language processing (NLP) is a powerful tool supporting the generation of Real-World Evidence (RWE). There is no NLP system that enables the extensive querying of parameters specific to multiple myeloma (MM) out of unstructured medical reports. We therefore created a MM-specific ontology to accelerate the information extraction (IE) out of unstructured text. Methods: Our MM ontology consists of extensive MM-specific and hierarchically structured attributes and values. We implemented "A Rule-based Information Extraction System" (ARIES) that uses this ontology. We evaluated ARIES on 200 randomly selected medical reports of patients diagnosed with MM. Results: Our system achieved a high F1-Score of 0.92 on the evaluation dataset with a precision of 0.87 and recall of 0.98. Conclusions: Our rule-based IE system enables the comprehensive querying of medical reports. The IE accelerates the extraction of data and enables clinicians to faster generate RWE on hematological issues. RWE helps clinicians to make decisions in an evidence-based manner. Our tool easily accelerates the integration of research evidence into everyday clinical practice.}, language = {en} } @article{GehrkeBalbachRauchetal.2019, author = {Gehrke, Alexander and Balbach, Nico and Rauch, Yong-Mi and Degkwitz, Andreas and Puppe, Frank}, title = {Erkennung von handschriftlichen Unterstreichungen in Alten Drucken}, series = {Bibliothek Forschung und Praxis}, volume = {43}, journal = {Bibliothek Forschung und Praxis}, number = {3}, issn = {1865-7648}, doi = {10.1515/bfp-2019-2083}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-193377}, pages = {447 -- 452}, year = {2019}, abstract = {Die Erkennung handschriftlicher Artefakte wie Unterstreichungen in Buchdrucken erm{\"o}glicht R{\"u}ckschl{\"u}sse auf das Rezeptionsverhalten und die Provenienzgeschichte und wird auch f{\"u}r eine OCR ben{\"o}tigt. Dabei soll zwischen handschriftlichen Unterstreichungen und waagerechten Linien im Druck (z. B. Trennlinien usw.) unterschieden werden, da letztere nicht ausgezeichnet werden sollen. Im Beitrag wird ein Ansatz basierend auf einem auf Unterstreichungen trainierten Neuronalen Netz gem{\"a}ß der U-Net Architektur vorgestellt, dessen Ergebnisse in einem zweiten Schritt mit heuristischen Regeln nachbearbeitet werden. Die Evaluationen zeigen, dass Unterstreichungen sehr gut erkannt werden, wenn bei der Binarisierung der Scans nicht zu viele Pixel der Unterstreichung wegen geringem Kontrast verloren gehen. Zuk{\"u}nftig sollen die Worte oberhalb der Unterstreichung mit OCR transkribiert werden und auch andere Artefakte wie handschriftliche Notizen in alten Drucken erkannt werden.}, language = {de} } @article{PetschkeStaab2019, author = {Petschke, Danny and Staab, Torsten E.M.}, title = {DDRS4PALS: a software for the acquisition and simulation of lifetime spectra using the DRS4 evaluation board}, series = {SoftwareX}, volume = {10}, journal = {SoftwareX}, doi = {10.1016/j.softx.2019.100261}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-202276}, pages = {100261}, year = {2019}, abstract = {Lifetime techniques are applied to diverse fields of study including materials sciences, semiconductor physics, biology, molecular biophysics and photochemistry. Here we present DDRS4PALS, a software for the acquisition and simulation of lifetime spectra using the DRS4 evaluation board (Paul Scherrer Institute, Switzerland) for time resolved measurements and digitization of detector output pulses. Artifact afflicted pulses can be corrected or rejected prior to the lifetime calculation to provide the generation of high-quality lifetime spectra, which are crucial for a profound analysis, i.e. the decomposition of the true information. Moreover, the pulses can be streamed on an (external) hard drive during the measurement and subsequently downloaded in the offline mode without being connected to the hardware. This allows the generation of various lifetime spectra at different configurations from one single measurement and, hence, a meaningful comparison in terms of analyzability and quality. Parallel processing and an integrated JavaScript based language provide convenient options to accelerate and automate time consuming processes such as lifetime spectra simulations.}, language = {en} } @unpublished{Dandekar2019, author = {Dandekar, Thomas}, title = {Biological heuristics applied to cosmology suggests a condensation nucleus as start of our universe and inflation cosmology replaced by a period of rapid Weiss domain-like crystal growth}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-183945}, pages = {24}, year = {2019}, abstract = {Cosmology often uses intricate formulas and mathematics to derive new theories and concepts. We do something different in this paper: We look at biological processes and derive from these heuristics so that the revised cosmology agrees with astronomical observations but does also agree with standard biological observations. We show that we then have to replace any type of singularity at the start of the universe by a condensation nucleus and that the very early period of the universe usually assumed to be inflation has to be replaced by a period of rapid crystal growth as in Weiss magnetization domains. Impressively, these minor modifications agree well with astronomical observations including removing the strong inflation perturbations which were never observed in the recent BICEP2 experiments. Furthermore, looking at biological principles suggests that such a new theory with a condensation nucleus at start and a first rapid phase of magnetization-like growth of the ordered, physical laws obeying lattice we live in is in fact the only convincing theory of the early phases of our universe that also is compatible with current observations. We show in detail in the following that such a process of crystal creation, breaking of new crystal seeds and ultimate evaporation of the present crystal readily leads over several generations to an evolution and selection of better, more stable and more self-organizing crystals. Moreover, this explains the "fine-tuning" question why our universe is fine-tuned to favor life: Our Universe is so self-organizing to have enough offspring and the detailed physics involved is at the same time highly favorable for all self-organizing processes including life. This biological theory contrasts with current standard inflation cosmologies. The latter do not perform well in explaining any phenomena of sophisticated structure creation or self-organization. As proteins can only thermodynamically fold by increasing the entropy in the solution around them we suggest for cosmology a condensation nucleus for a universe can form only in a "chaotic ocean" of string-soup or quantum foam if the entropy outside of the nucleus rapidly increases. We derive an interaction potential for 1 to n-dimensional strings or quantum-foams and show that they allow only 1D, 2D, 4D or octonion interactions. The latter is the richest structure and agrees to the E8 symmetry fundamental to particle physics and also compatible with the ten dimensional string theory E8 which is part of the M-theory. Interestingly, any other interactions of other dimensionality can be ruled out using Hurwitz compositional theorem. Crystallization explains also extremely well why we have only one macroscopic reality and where the worldlines of alternative trajectories exist: They are in other planes of the crystal and for energy reasons they crystallize mostly at the same time, yielding a beautiful and stable crystal. This explains decoherence and allows to determine the size of Planck´s quantum h (very small as separation of crystal layers by energy is extremely strong). Ultimate dissolution of real crystals suggests an explanation for dark energy agreeing with estimates for the "big rip". The halo distribution of dark matter favoring galaxy formation is readily explained by a crystal seed starting with unit cells made of normal and dark matter. That we have only matter and not antimatter can be explained as there may be right handed mattercrystals and left-handed antimatter crystals. Similarly, real crystals are never perfect and we argue that exactly such irregularities allow formation of galaxies, clusters and superclusters. Finally, heuristics from genetics suggest to look for a systems perspective to derive correct vacuum and Higgs Boson energies.}, language = {en} } @phdthesis{Peng2019, author = {Peng, Dongliang}, title = {An Optimization-Based Approach for Continuous Map Generalization}, edition = {1. Auflage}, publisher = {W{\"u}rzburg University Press}, address = {W{\"u}rzburg}, isbn = {978-3-95826-104-4}, doi = {10.25972/WUP-978-3-95826-105-1}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-174427}, school = {W{\"u}rzburg University Press}, pages = {xv, 132}, year = {2019}, abstract = {Maps are the main tool to represent geographical information. Geographical information is usually scale-dependent, so users need to have access to maps at different scales. In our digital age, the access is realized by zooming. As discrete changes during the zooming tend to distract users, smooth changes are preferred. This is why some digital maps are trying to make the zooming as continuous as they can. The process of producing maps at different scales with smooth changes is called continuous map generalization. In order to produce maps of high quality, cartographers often take into account additional requirements. These requirements are transferred to models in map generalization. Optimization for map generalization is important not only because it finds optimal solutions in the sense of the models, but also because it helps us to evaluate the quality of the models. Optimization, however, becomes more delicate when we deal with continuous map generalization. In this area, there are requirements not only for a specific map but also for relations between maps at difference scales. This thesis is about continuous map generalization based on optimization. First, we show the background of our research topics. Second, we find optimal sequences for aggregating land-cover areas. We compare the A\$^{\!\star}\$\xspace algorithm and integer linear programming in completing this task. Third, we continuously generalize county boundaries to provincial boundaries based on compatible triangulations. We morph between the two sets of boundaries, using dynamic programming to compute the correspondence. Fourth, we continuously generalize buildings to built-up areas by aggregating and growing. In this work, we group buildings with the help of a minimum spanning tree. Fifth, we define vertex trajectories that allow us to morph between polylines. We require that both the angles and the edge lengths change linearly over time. As it is impossible to fulfill all of these requirements simultaneously, we mediate between them using least-squares adjustment. Sixth, we discuss the performance of some commonly used data structures for a specific spatial problem. Seventh, we conclude this thesis and present open problems.}, subject = {Generalisierung }, language = {en} }