@techreport{RossiMaurelliUnnithanetal.2021, author = {Rossi, Angelo Pio and Maurelli, Francesco and Unnithan, Vikram and Dreger, Hendrik and Mathewos, Kedus and Pradhan, Nayan and Corbeanu, Dan-Andrei and Pozzobon, Riccardo and Massironi, Matteo and Ferrari, Sabrina and Pernechele, Claudia and Paoletti, Lorenzo and Simioni, Emanuele and Maurizio, Pajola and Santagata, Tommaso and Borrmann, Dorit and N{\"u}chter, Andreas and Bredenbeck, Anton and Zevering, Jasper and Arzberger, Fabian and Reyes Mantilla, Camilo Andr{\´e}s}, title = {DAEDALUS - Descent And Exploration in Deep Autonomy of Lava Underground Structures}, isbn = {978-3-945459-33-1}, issn = {1868-7466}, doi = {10.25972/OPUS-22791}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-227911}, pages = {188}, year = {2021}, abstract = {The DAEDALUS mission concept aims at exploring and characterising the entrance and initial part of Lunar lava tubes within a compact, tightly integrated spherical robotic device, with a complementary payload set and autonomous capabilities. The mission concept addresses specifically the identification and characterisation of potential resources for future ESA exploration, the local environment of the subsurface and its geologic and compositional structure. A sphere is ideally suited to protect sensors and scientific equipment in rough, uneven environments. It will house laser scanners, cameras and ancillary payloads. The sphere will be lowered into the skylight and will explore the entrance shaft, associated caverns and conduits. Lidar (light detection and ranging) systems produce 3D models with high spatial accuracy independent of lighting conditions and visible features. Hence this will be the primary exploration toolset within the sphere. The additional payload that can be accommodated in the robotic sphere consists of camera systems with panoramic lenses and scanners such as multi-wavelength or single-photon scanners. A moving mass will trigger movements. The tether for lowering the sphere will be used for data communication and powering the equipment during the descending phase. Furthermore, the connector tether-sphere will host a WIFI access point, such that data of the conduit can be transferred to the surface relay station. During the exploration phase, the robot will be disconnected from the cable, and will use wireless communication. Emergency autonomy software will ensure that in case of loss of communication, the robot will continue the nominal mission.}, subject = {Mond}, 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{HeinLatoschikWienrich2022, author = {Hein, Rebecca M. and Latoschik, Marc Erich and Wienrich, Carolin}, title = {Inter- and transcultural learning in cocial virtual reality: a proposal for an inter- and transcultural virtual object database to be used in the implementation, reflection, and evaluation of virtual encounters}, series = {Multimodal Technologies and Interaction}, volume = {6}, journal = {Multimodal Technologies and Interaction}, number = {7}, issn = {2414-4088}, doi = {10.3390/mti6070050}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-278974}, year = {2022}, abstract = {Visual stimuli are frequently used to improve memory, language learning or perception, and understanding of metacognitive processes. However, in virtual reality (VR), there are few systematically and empirically derived databases. This paper proposes the first collection of virtual objects based on empirical evaluation for inter-and transcultural encounters between English- and German-speaking learners. We used explicit and implicit measurement methods to identify cultural associations and the degree of stereotypical perception for each virtual stimuli (n = 293) through two online studies, including native German and English-speaking participants. The analysis resulted in a final well-describable database of 128 objects (called InteractionSuitcase). In future applications, the objects can be used as a great interaction or conversation asset and behavioral measurement tool in social VR applications, especially in the field of foreign language education. For example, encounters can use the objects to describe their culture, or teachers can intuitively assess stereotyped attitudes of the encounters.}, 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{ZimmererFischbachLatoschik2018, author = {Zimmerer, Chris and Fischbach, Martin and Latoschik, Marc Erich}, title = {Semantic Fusion for Natural Multimodal Interfaces using Concurrent Augmented Transition Networks}, series = {Multimodal Technologies and Interaction}, volume = {2}, journal = {Multimodal Technologies and Interaction}, number = {4}, issn = {2414-4088}, doi = {10.3390/mti2040081}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-197573}, year = {2018}, abstract = {Semantic fusion is a central requirement of many multimodal interfaces. Procedural methods like finite-state transducers and augmented transition networks have proven to be beneficial to implement semantic fusion. They are compliant with rapid development cycles that are common for the development of user interfaces, in contrast to machine-learning approaches that require time-costly training and optimization. We identify seven fundamental requirements for the implementation of semantic fusion: Action derivation, continuous feedback, context-sensitivity, temporal relation support, access to the interaction context, as well as the support of chronologically unsorted and probabilistic input. A subsequent analysis reveals, however, that there is currently no solution for fulfilling the latter two requirements. As the main contribution of this article, we thus present the Concurrent Cursor concept to compensate these shortcomings. In addition, we showcase a reference implementation, the Concurrent Augmented Transition Network (cATN), that validates the concept's feasibility in a series of proof of concept demonstrations as well as through a comparative benchmark. The cATN fulfills all identified requirements and fills the lack amongst previous solutions. It supports the rapid prototyping of multimodal interfaces by means of five concrete traits: Its declarative nature, the recursiveness of the underlying transition network, the network abstraction constructs of its description language, the utilized semantic queries, and an abstraction layer for lexical information. Our reference implementation was and is used in various student projects, theses, as well as master-level courses. It is openly available and showcases that non-experts can effectively implement multimodal interfaces, even for non-trivial applications in mixed and virtual reality.}, 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{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{Budig2018, author = {Budig, Benedikt}, title = {Extracting Spatial Information from Historical Maps: Algorithms and Interaction}, edition = {1. Auflage}, publisher = {W{\"u}rzburg University Press}, address = {W{\"u}rzburg}, isbn = {978-3-95826-092-4}, doi = {10.25972/WUP-978-3-95826-093-1}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-160955}, school = {W{\"u}rzburg University Press}, pages = {viii, 160}, year = {2018}, abstract = {Historical maps are fascinating documents and a valuable source of information for scientists of various disciplines. Many of these maps are available as scanned bitmap images, but in order to make them searchable in useful ways, a structured representation of the contained information is desirable. This book deals with the extraction of spatial information from historical maps. This cannot be expected to be solved fully automatically (since it involves difficult semantics), but is also too tedious to be done manually at scale. The methodology used in this book combines the strengths of both computers and humans: it describes efficient algorithms to largely automate information extraction tasks and pairs these algorithms with smart user interactions to handle what is not understood by the algorithm. The effectiveness of this approach is shown for various kinds of spatial documents from the 16th to the early 20th century.}, subject = {Karte}, language = {en} } @article{RodriguesWeissHewigetal.2021, author = {Rodrigues, Johannes and Weiß, Martin and Hewig, Johannes and Allen, John J. B.}, title = {EPOS: EEG Processing Open-Source Scripts}, series = {Frontiers in Neuroscience}, volume = {15}, journal = {Frontiers in Neuroscience}, issn = {1662-453X}, doi = {10.3389/fnins.2021.660449}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-240221}, year = {2021}, abstract = {Background: Since the replication crisis, standardization has become even more important in psychological science and neuroscience. As a result, many methods are being reconsidered, and researchers' degrees of freedom in these methods are being discussed as a potential source of inconsistencies across studies. New Method: With the aim of addressing these subjectivity issues, we have been working on a tutorial-like EEG (pre-)processing pipeline to achieve an automated method based on the semi-automated analysis proposed by Delorme and Makeig. Results: Two scripts are presented and explained step-by-step to perform basic, informed ERP and frequency-domain analyses, including data export to statistical programs and visual representations of the data. The open-source software EEGlab in MATLAB is used as the data handling platform, but scripts based on code provided by Mike Cohen (2014) are also included. Comparison with existing methods: This accompanying tutorial-like article explains and shows how the processing of our automated pipeline affects the data and addresses, especially beginners in EEG-analysis, as other (pre)-processing chains are mostly targeting rather informed users in specialized areas or only parts of a complete procedure. In this context, we compared our pipeline with a selection of existing approaches. Conclusion: The need for standardization and replication is evident, yet it is equally important to control the plausibility of the suggested solution by data exploration. Here, we provide the community with a tool to enhance the understanding and capability of EEG-analysis. We aim to contribute to comprehensive and reliable analyses for neuro-scientific research.}, language = {en} } @article{HirthSeufertLangeetal.2021, author = {Hirth, Matthias and Seufert, Michael and Lange, Stanislav and Meixner, Markus and Tran-Gia, Phuoc}, title = {Performance evaluation of hybrid crowdsensing and fixed sensor systems for event detection in urban environments}, series = {Sensors}, volume = {21}, journal = {Sensors}, number = {17}, issn = {1424-8220}, doi = {10.3390/s21175880}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-245245}, year = {2021}, abstract = {Crowdsensing offers a cost-effective way to collect large amounts of environmental sensor data; however, the spatial distribution of crowdsensing sensors can hardly be influenced, as the participants carry the sensors, and, additionally, the quality of the crowdsensed data can vary significantly. Hybrid systems that use mobile users in conjunction with fixed sensors might help to overcome these limitations, as such systems allow assessing the quality of the submitted crowdsensed data and provide sensor values where no crowdsensing data are typically available. In this work, we first used a simulation study to analyze a simple crowdsensing system concerning the detection performance of spatial events to highlight the potential and limitations of a pure crowdsourcing system. The results indicate that even if only a small share of inhabitants participate in crowdsensing, events that have locations correlated with the population density can be easily and quickly detected using such a system. On the contrary, events with uniformly randomly distributed locations are much harder to detect using a simple crowdsensing-based approach. A second evaluation shows that hybrid systems improve the detection probability and time. Finally, we illustrate how to compute the minimum number of fixed sensors for the given detection time thresholds in our exemplary scenario.}, language = {en} }