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Now showing 1 - 10 of 133
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    Comparative Verification of the Digital Library of Mathematical Functions and Computer Algebra Systems
    (Berlin ; Heidelberg : Springer, 2022) Greiner-Petter, André; Cohl, Howard S.; Youssef, Abdou; Schubotz, Moritz; Trost, Avi; Dey, Rajen; Aizawa, Akiko; Gipp, Bela; Fisman, Dana; Rosu, Grigore
    Digital mathematical libraries assemble the knowledge of years of mathematical research. Numerous disciplines (e.g., physics, engineering, pure and applied mathematics) rely heavily on compendia gathered findings. Likewise, modern research applications rely more and more on computational solutions, which are often calculated and verified by computer algebra systems. Hence, the correctness, accuracy, and reliability of both digital mathematical libraries and computer algebra systems is a crucial attribute for modern research. In this paper, we present a novel approach to verify a digital mathematical library and two computer algebra systems with one another by converting mathematical expressions from one system to the other. We use our previously developed conversion tool (referred to as ) to translate formulae from the NIST Digital Library of Mathematical Functions to the computer algebra systems Maple and Mathematica. The contributions of our presented work are as follows: (1) we present the most comprehensive verification of computer algebra systems and digital mathematical libraries with one another; (2) we significantly enhance the performance of the underlying translator in terms of coverage and accuracy; and (3) we provide open access to translations for Maple and Mathematica of the formulae in the NIST Digital Library of Mathematical Functions.
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    Data Protection Impact Assessments in Practice: Experiences from Case Studies
    (Berlin ; Heidelberg : Springer, 2022) Friedewald, Michael; Schiering, Ina; Martin, Nicholas; Hallinan, Dara; Katsikas, Sokratis; Lambrinoudakis, Costas; Cuppens, Nora; Mylopoulos, John; Kalloniatis, Christos; Meng, Weizhi; Furnell, Steven; Pallas, Frank; Pohle, Jörg; Sasse, M. Angela; Abie, Habtamu; Ranise, Silvio; Verderame, Luca; Cambiaso, Enrico; Vidal, Jorge Maestre; Monge, Marco Antonio Sotelo
    In the context of the project A Data Protection Impact Assessment (DPIA) Tool for Practical Use in Companies and Public Administration an operationalization for Data Protection Impact Assessments was developed based on the approach of Forum Privatheit. This operationalization was tested and refined during twelve tests with startups, small- and medium sized enterprises, corporations and public bodies. This paper presents the operationalization and summarizes the experience from the tests.
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    Basic material and technology investigations for material bonded hybrids by continuous hybrid profile fabrication
    (London [u.a.] : Institute of Physics, 2021) Schubert, K.; Gedan-Smolka, M.; Marschner, A.; Rietzschel, T.; Uhlig, K.; Löpitz, D.; Wagner, D.; Knobloch, M.; Karjust, Krist; Otto, Tauno; Kübarsepp, Jakob; Hussainova, Irina
    The development of multi-material hybrids by injection molding has been studied very intensively at the IPF in the past. For that, a material bonding between the different substrates was achieved by using a newly developed two-step curing powder coating material as latent reactive adhesive. The aim of the project “Hybrid Pultrusion” was to perform a novel approach for the fabrication of material bonded metal-plastic joints (profiles) in a modified pultrusion process. Therefore, powder pre-coated steel coil is combined with a glass-fiber reinforced epoxy resin matrix. For initial basic studies, the impregnated fiber material has been applied on the pre-coated steel sheets using the Resin Transfer Molding process (RTM-process). It was proved via lap shear tests, that this procedure resulted in very high adhesive strengths up to 35 MPa resulting from the formation of a covalent matrix-steel bonding as well. In addition, the failure mechanism was subsequently studied. Furthermore, by adapting the successful material combination to the pultrusion process it was demonstrated that material bonded hybrids can be achieved even under these continuous processing conditions.
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    Meetings and Mood-Related or Not? Insights from Student Software Projects
    (New York : Association for Computing Machinery, 2022) Klünder, Jil; Karras, Oliver; Madeiral, Fernanda; Lassenius, Casper
    [Background:] Teamwork, coordination, and communication are a prerequisite for the timely completion of a software project. Meetings as a facilitator for coordination and communication are an established medium for information exchange. Analyses of meetings in software projects have shown that certain interactions in these meetings, such as proactive statements followed by supportive ones, influence the mood and motivation of a team, which in turn affects its productivity. So far, however, research has focused only on certain interactions at a detailed level, requiring a complex and fine-grained analysis of a meeting itself. [Aim:] In this paper, we investigate meetings from a more abstract perspective, focusing on the polarity of the statements, i.e., whether they appear to be positive, negative, or neutral. [Method:] We analyze the relationship between the polarity of statements in meetings and different social aspects, including conflicts as well as the mood before and after a meeting. [Results:] Our results emerge from 21 student software project meetings and show some interesting insights: (1) Positive mood before a meeting is both related to the amount of positive statements in the beginning, as well as throughout the whole meeting, (2) negative mood before the meeting only influences the amount of negative statements in the first quarter of the meeting, but not the whole meeting, and (3) the amount of positive and negative statements during the meeting has no influence on the mood afterwards. [Conclusions:] We conclude that the behaviour in meetings might rather influence short-term emotional states (feelings) than long-term emotional states (mood), which are more important for the project.
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    Knowledge Extraction for Art History: the Case of Vasari’s The Lives of The Artists (1568)
    (Aachen, Germany : RWTH Aachen, 2022) Santini, Cristian; Tan, Mary Ann; Tietz, Tabea; Bruns, Oleksandra; Posthumus, Etienne; Sack, Harald; Paschke, Adrian; Rehm, Georg; Neudecker, Clemens; Pintscher, Lydia
    Knowledge Extraction (KE) techniques are used to convert unstructured information present in texts to Knowledge Graphs (KGs) which can be queried and explored. Despite their potential for cultural heritage domains, such as Art History, these techniques often encounter limitations if applied to domain-specific data. In this paper we present the main challenges that KE has to face on art-historical texts, by using as case study Giorgio Vasari's The Lives of The Artists. This paper discusses the following NLP tasks for art-historical texts, namely entity recognition and linking, coreference resolution, time extraction, motif extraction and artwork extraction. Several strategies to annotate art-historical data for these tasks and evaluate NLP models are also proposed.
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    On the Impact of Temporal Representations on Metaphor Detection
    (Paris : European Language Resources Association (ELRA), 2022) Giorgio Ottolina; Matteo Palmonari; Manuel Vimercati; Mehwish Alam; Calzolari, Nicoletta; Béchet, Frédéric; Blache, Philippe; Choukri, Khalid; Cieri, Christopher; Declerck, Thierry; Goggi, Sara; Isahara, Hitoshi; Maegaard, Bente; Mariani, Joseph; Mazo, Hélène; Odijk, Jan; Piperidis, Stelios
    State-of-the-art approaches for metaphor detection compare their literal - or core - meaning and their contextual meaning using metaphor classifiers based on neural networks. However, metaphorical expressions evolve over time due to various reasons, such as cultural and societal impact. Metaphorical expressions are known to co-evolve with language and literal word meanings, and even drive, to some extent, this evolution. This poses the question of whether different, possibly time-specific, representations of literal meanings may impact the metaphor detection task. To the best of our knowledge, this is the first study that examines the metaphor detection task with a detailed exploratory analysis where different temporal and static word embeddings are used to account for different representations of literal meanings. Our experimental analysis is based on three popular benchmarks used for metaphor detection and word embeddings extracted from different corpora and temporally aligned using different state-of-the-art approaches. The results suggest that the usage of different static word embedding methods does impact the metaphor detection task and some temporal word embeddings slightly outperform static methods. However, the results also suggest that temporal word embeddings may provide representations of the core meaning of the metaphor even too close to their contextual meaning, thus confusing the classifier. Overall, the interaction between temporal language evolution and metaphor detection appears tiny in the benchmark datasets used in our experiments. This suggests that future work for the computational analysis of this important linguistic phenomenon should first start by creating a new dataset where this interaction is better represented.
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    Improving Zero-Shot Text Classification with Graph-based Knowledge Representations
    (Aachen, Germany : RWTH Aachen, 2022) Hoppe, Fabian; Hartig, Olaf; Seneviratne, Oshani
    Insufficient training data is a key challenge for text classification. In particular, long-tail class distributions and emerging, new classes do not provide any training data for specific classes. Therefore, such a zeroshot setting must incorporate additional, external knowledge to enable transfer learning by connecting the external knowledge of previously unseen classes to texts. Recent zero-shot text classifier utilize only distributional semantics defined by large language models and based on class names or natural language descriptions. This implicit knowledge contains ambiguities, is not able to capture logical relations nor is it an efficient representation of factual knowledge. These drawbacks can be avoided by introducing explicit, external knowledge. Especially, knowledge graphs provide such explicit, unambiguous, and complementary, domain specific knowledge. Hence, this thesis explores graph-based knowledge as additional modality for zero-shot text classification. Besides a general investigation of this modality, the influence on the capabilities of dealing with domain shifts by including domain-specific knowledge is explored.
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    Toward a Comparison Framework for Interactive Ontology Enrichment Methodologies
    (Aachen, Germany : RWTH Aachen, 2022) Vrolijk, Jarno; Reklos, Ioannis; Vafaie, Mahsa; Massari, Arcangelo; Mohammadi, Maryam; Rudolph, Sebastian; Fu, Bo; Lambrix, Patrick; Pesquita, Catia
    The growing demand for well-modeled ontologies in diverse application areas increases the need for intuitive interaction techniques that support human domain experts in ontology modeling and enrichment tasks, such that quality expectations are met. Beyond the correctness of the specified information, the quality of an ontology depends on its (relative) completeness, i.e., whether the ontology contains all the necessary information to draw expected inferences. On an abstract level, the Ontology Enrichment problem consists of identifying and filling the gap between information that can be logically inferred from the ontology and the information expected to be inferable by the user. To this end, numerous approaches have been described in the literature, providing methodologies from the fields of Formal Semantics and Automated Reasoning targeted at eliciting knowledge from human domain experts. These approaches vary greatly in many aspects and their applicability typically depends on the specifics of the concrete modeling scenario at hand. Toward a better understanding of the landscape of methodological possibilities, this position paper proposes a framework consisting of multiple performance dimensions along which existing and future approaches to interactive ontology enrichment can be characterized. We apply our categorization scheme to a selection of methodologies from the literature. In light of this comparison, we address the limitations of the methods and propose directions for future work.
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    Hollow square core fiber sensor for physical parameters measurement
    (Bristol : IOP Publ., 2022) Pereira, Diana; Bierlich, Jörg; Kobelke, Jens; Ferreira, Marta S.
    The measurement of physical parameters is important in many current applications, since they often rely on these measurands to operate with the due quality and the necessary safety. In this work, a simple and robust optical fiber sensor based on an antiresonant hollow square core fiber (HSCF) is proposed to measure simultaneously temperature, strain, and curvature. The proposed sensor was designed in a transmission configuration where a segment of HSCF, with a 10 mm length, was spliced between two single mode fibers. In this sensor, a cladding modal interference (CMI) and a Mach-Zehnder interference (MZI) are enhanced along with the antiresonance (AR) guidance. All the present mechanisms exhibit different responses towards the physical parameters. For the temperature, sensitivities of 32.8 pm/°C, 18.9 pm/°C, and 15.7 pm/°C were respectively attained for the MZI, AR, and CMI. As for the strain, sensitivities of 0.45 pm/μϵ, -0.93 pm/μϵ, and -2.72 pm/μϵ were acquired for the MZI, AR and CMI respectively. Meanwhile, for the curvature measurements, two regions of analysis were considered. In the first region (0 m-1 - 0.7 m-1) sensitivities of 0.033 nm/m-1, -0.27 nm/m-1, and -2.21 nm/m-1 were achieved, whilst for the second region (0.7 m-1 - 1.5 m-1) sensitivities of 0.067 nm/m-1, -0.63 nm/m-1, and -0.49 nm/m-1 were acquired for the MZI, AR and CMI, respectively.
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    Capillary based hybrid fiber sensor in a balloon-like shape for simultaneous measurement of displacement and temperature
    (Bristol : IOP Publ., 2022) Santos, João P.; Bierlich, Jörg; Kobelke, Jens; Ferreira, Marta S.
    In this work, a hybrid sensor based on a silica capillary in a balloon-like shape for simultaneous measurement of displacement and temperature is proposed for the first time, to the best of our knowledge. The sensor is fabricated by splicing a segment of a hollow core fiber between two single mode fibers (SMF) and by bending the fiber in a balloon shape with the capillary at the top-center position. In a transmission scheme, the SMF-capillary-SMF configuration excites an antiresonant (AR) guidance and the balloon shape enhances a Mach-Zehnder interferometer (MZI). The different responses of the interferometers to external displacement and temperature variations are conducive to a hybrid application of the sensor for simultaneous measurement of these parameters. Experimental results show that, for a capillary length of 1.2 cm and a balloon length of 4 cm, AR is insensitive to displacement and its sensitivity to temperature is 14.3 pm/°C, while the MZI has a sensitivity to displacement of 1.68 nm/mm and twice the sensitivity of AR to temperature, of 28.6 pm/°C. The proposed fiber sensor consists of only one sensing element in one configuration exciting two interferometers at the same time, which makes it of simple fabrication as well as low cost.