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Now showing 1 - 10 of 37
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    Audio Ontologies for Intangible Cultural Heritage
    (Bramhall, Stockport ; EasyChair Ltd., 2022-04-12) Tan, Mary Ann; Posthumus, Etienne; Sack, Harald
    Cultural heritage portals often contain intangible objects digitized as audio files. This paper presents and discusses the adaptation of existing audio ontologies intended for non-cultural heritage applications. The resulting alignment of the German Digital Library-Europeana Data Model (DDB-EDM) with Music Ontology (MO) and Audio Commons Ontology (ACO) is presented.
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    Unveiling Relations in the Industry 4.0 Standards Landscape Based on Knowledge Graph Embeddings
    (Cham : Springer, 2020) Rivas, Ariam; Grangel-González, Irlán; Collarana, Diego; Lehmann, Jens; Vidal, Maria-Esther; Hartmann, Sven; Küng, Josef; Kotsis, Gabriele; Tjoa, A Min; Khalil, Ismail
    Industry 4.0 (I4.0) standards and standardization frameworks have been proposed with the goal of empowering interoperability in smart factories. These standards enable the description and interaction of the main components, systems, and processes inside of a smart factory. Due to the growing number of frameworks and standards, there is an increasing need for approaches that automatically analyze the landscape of I4.0 standards. Standardization frameworks classify standards according to their functions into layers and dimensions. However, similar standards can be classified differently across the frameworks, producing, thus, interoperability conflicts among them. Semantic-based approaches that rely on ontologies and knowledge graphs, have been proposed to represent standards, known relations among them, as well as their classification according to existing frameworks. Albeit informative, the structured modeling of the I4.0 landscape only provides the foundations for detecting interoperability issues. Thus, graph-based analytical methods able to exploit knowledge encoded by these approaches, are required to uncover alignments among standards. We study the relatedness among standards and frameworks based on community analysis to discover knowledge that helps to cope with interoperability conflicts between standards. We use knowledge graph embeddings to automatically create these communities exploiting the meaning of the existing relationships. In particular, we focus on the identification of similar standards, i.e., communities of standards, and analyze their properties to detect unknown relations. We empirically evaluate our approach on a knowledge graph of I4.0 standards using the Trans∗ family of embedding models for knowledge graph entities. Our results are promising and suggest that relations among standards can be detected accurately.
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    Graphite modified epoxy-based adhesive for joining of aluminium and PP/graphite composites
    (New York, NY [u.a.] : Taylor & Francis, 2020) Rzeczkowski, P.; Pötschke, Petra; Fischer, M.; Kühnert, I.; Krause, Beate
    A graphite-modified adhesive was developed in order to simultaneously enhance the thermal conductivity and the strength of an adhesive joint. The thermal conductivity through the joint was investigated by using highly filled PP/graphite composite substrates, which were joined with an epoxy adhesive of different layer thicknesses. Similar measurements were carried out with a constant adhesive layer thickness, whilst applying an epoxy adhesive modified with expanded graphite (EG) (6, 10, and 20 wt%). By reducing the adhesive layer thickness or modifying the adhesive with conductive fillers, a significant increase of the thermal conductivity through the joint was achieved. The examination of the mechanical properties of the modified adhesives was carried out by tensile tests (adhesive only), lap-shear tests, and fracture energy tests (mode 1) with aluminium substrates. Modification of the adhesive with EG led to an increase of the tensile lap-shear strength and the adhesive fracture energy (mode 1) of the joint. In addition, burst pressure tests were performed to determine the strength of the joint in a complex component. The strength of the joint increased with the graphite content in the PP substrate and in the epoxy adhesive.
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    Ontology Design for Pharmaceutical Research Outcomes
    (Cham : Springer, 2020) Say, Zeynep; Fathalla, Said; Vahdati, Sahar; Lehmann, Jens; Auer, Sören; Hall, Mark; Merčun, Tanja; Risse, Thomas; Duchateau, Fabien
    The network of scholarly publishing involves generating and exchanging ideas, certifying research, publishing in order to disseminate findings, and preserving outputs. Despite enormous efforts in providing support for each of those steps in scholarly communication, identifying knowledge fragments is still a big challenge. This is due to the heterogeneous nature of the scholarly data and the current paradigm of distribution by publishing (mostly document-based) over journal articles, numerous repositories, and libraries. Therefore, transforming this paradigm to knowledge-based representation is expected to reform the knowledge sharing in the scholarly world. Although many movements have been initiated in recent years, non-technical scientific communities suffer from transforming document-based publishing to knowledge-based publishing. In this paper, we present a model (PharmSci) for scholarly publishing in the pharmaceutical research domain with the goal of facilitating knowledge discovery through effective ontology-based data integration. PharmSci provides machine-interpretable information to the knowledge discovery process. The principles and guidelines of the ontological engineering have been followed. Reasoning-based techniques are also presented in the design of the ontology to improve the quality of targeted tasks for data integration. The developed ontology is evaluated with a validation process and also a quality verification method.
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    Compact representations for efficient storage of semantic sensor data
    (Dordrecht : Springer Science + Business Media B.V, 2021) Karim, Farah; Vidal, Maria-Esther; Auer, Sören
    Nowadays, there is a rapid increase in the number of sensor data generated by a wide variety of sensors and devices. Data semantics facilitate information exchange, adaptability, and interoperability among several sensors and devices. Sensor data and their meaning can be described using ontologies, e.g., the Semantic Sensor Network (SSN) Ontology. Notwithstanding, semantically enriched, the size of semantic sensor data is substantially larger than raw sensor data. Moreover, some measurement values can be observed by sensors several times, and a huge number of repeated facts about sensor data can be produced. We propose a compact or factorized representation of semantic sensor data, where repeated measurement values are described only once. Furthermore, these compact representations are able to enhance the storage and processing of semantic sensor data. To scale up to large datasets, factorization based, tabular representations are exploited to store and manage factorized semantic sensor data using Big Data technologies. We empirically study the effectiveness of a semantic sensor’s proposed compact representations and their impact on query processing. Additionally, we evaluate the effects of storing the proposed representations on diverse RDF implementations. Results suggest that the proposed compact representations empower the storage and query processing of sensor data over diverse RDF implementations, and up to two orders of magnitude can reduce query execution time.
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    Concept for Setting up an LTA Working Group in the NFDI Section "Common Infrastructures"
    (Zenodo, 2022-04-12) Bach, Felix; Degkwitz, Andreas; Horstmann, Wolfram; Leinen, Peter; Puchta, Michael; Stäcker, Thomas
    NFDI consortia have a variety of disparate and distributed information infrastructures, many of which are as yet only loosely or poorly connected. A major goal is to create a Research Data Commons (RDC) . The RDC concept1 includes, for example, shared cloud services, an application layer with access to high-performance computing (HPC), collaborative workspaces, terminology services, and a common authentication and authorization infrastructure (AAI). The necessary interoperability of services requires, in particular, agreement on protocols and standards, the specification of workflows and interfaces, and the definition of long-term sustainable responsibilities for overarching services and deliverables. Infrastructure components are often well-tested in NFDI on a domain-specific basis, but are quite heterogeneous and diverse between domains. LTA for digital resources has been a recurring problem for well over 30 years and has not been conclusively solved to date, getting urgency with the exponential growth of research data, whether it involves demands from funders - the DFG requires 10 years of retention - or digital artifacts that must be preserved indefinitely as digital cultural heritage. Against this background, the integration of the LTA into the RDC of the NFDI is an urgent desideratum in order to be able to guarantee the permanent usability of research data. A distinction must be2 made between the archiving of the digital objects as bitstreams (this can be numeric or textual data or complex objects such as models), which represents a first step towards long-term usability, and the archiving of the semantic and software-technical context of the digital original objects, which entails far more effort. Beyond the technical embedding of the LTA in the system environment of a multi-cloud-based infrastructure, a number of technically differentiated requirements of the NFDI's subject consortia are part of the development of a basic service for the LTA and for the re-use of research data.3 The need for funding for the development of a basic LTA service for the NFDI consortia results primarily from the additional costs associated with the technical and organizational development of a cross-NFDI, decentralized network structure for LTA and the sustainable subsequent use of research data. It is imperative that the technical actors are able to act within the network as a technology-oriented community, and that they can provide their own services as part of the support for also within a federated infrastructure. The working group "Long Term Archiving" (LTA) is to develop the requirements of the technical consortia for LTA and, on this basis, strategic approaches for the implementation of a basic service LTA. The working group consists of members of various NFDI consortia covering the humanities, natural science and engineering disciplines and experts from a variety of pertinent infrastructures with strong overall connections to the nestor long-term archiving competence network. The close linkage of NFDI consortia with experienced4 partners in the field of LTA ensures that a) the relevant technical state-of-the-art is present in the group and b) the knowledge of data producers about contexts of origin and data users interact directly. This composition enables the team to take an overarching view that spans the requirements of the disciplines and consortia, also takes into account interdisciplinary needs, and at the same time brings in the existing know-how in the infrastructure sector.
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    Simultaneous statistical inference for epigenetic data
    (Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2015) Schildknecht, Konstantin; Olek, Sven; Dickhaus, Thorsten
    Epigenetic research leads to complex data structures. Since parametric model assumptions for the distribution of epigenetic data are hard to verify we introduce in the present work a nonparametric statistical framework for two-group comparisons. Furthermore, epigenetic analyses are often performed at various genetic loci simultaneously. Hence, in order to be able to draw valid conclusions for specific loci, an appropriate multiple testing correction is necessary. Finally, with technologies available for the simultaneous assessment of many interrelated biological parameters (such as gene arrays), statistical approaches also need to deal with a possibly unknown dependency structure in the data. Our statistical approach to the nonparametric comparison of two samples with independent multivariate observables is based on recently developed multivariate multiple permutation tests. We adapt their theory in order to cope with families of hypotheses regarding relative effects. Our results indicate that the multivariate multiple permutation test keeps the pre-assigned type I error level for the global null hypothesis. In combination with the closure principle, the family-wise error rate for the simultaneous test of the corresponding locus/parameter-specific null hypotheses can be controlled. In applications we demonstrate that group differences in epigenetic data can be detected reliably with our methodology.
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    Methods to characterize the dispersability of carbon nanotubes and their length distribution
    (Weinheim : Wiley-VCH Verl., 2012) Krause, Beate; Mende, Mandy; Petzold, Gudrun; Boldt, Regine; Pötschke, Petra
    Two main properties of carbon nanotube (CNT) materials are discussed in this contribution. First, a method to characterize the dispersability of CNT materials in aqueous surfactant solutions in presented, which also allows conclusions towards the dispersability in other media, like polymer melts. On the other hand it is shown, how the length of CNTs before and after processing, e.g., after melt mixing with thermoplastics, can be quantified. Both methods are illustrated with examples and the practical relevance is shown. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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    The effect of branched carbon nanotubes as reinforcing nano-filler in polymer nanocomposites
    (London : Elsevier, 2022) Thompson, S.M.; Talò, M.; Krause, Beate; Janke, A.; Lanzerotti, M.; Capps, J.; Lanzara, G.; Lacarbonara, W.
    This work discusses the mechanical and dissipative properties of nanocomposite materials made of a high-performance thermoplastic polymer (polybutylene terephthalate, PBT) integrated with branched carbon nanotubes (bCNTs) as nanofiller. The storage and loss moduli as well as the loss factor/damping ratio of the nanocomposites are experimentally characterized for increasing bCNT weight fractions (wt% bCNT) upon variations of the input cyclic strain amplitude and of the input frequency, respectively. The trends obtained for the nanocomposites mechanical properties indicate improvements both in storage and loss modulus by increasing the bCNT weight fraction from 0.5% to 2%. The striking differences between the damping capacities exhibited by CNT/polymer and bCNT/polymer nanocomposites are discussed to shed light onto the different underlined mechanics of the nanocomposites. Due to the stick–slip relative sliding motion of the polymer chains with respect to the straight CNTs, CNT/PBT nanocomposites are known to exhibit a peak in the damping vs. strain amplitude curves, past which, the damping capacity shows a monotonically increasing trend due to the conjectured sliding of the polymer crystals. On the other hand, we show for the first time that bCNT/PBT nanocomposites do not exhibit a peak in the damping capacity but rather a plateau after an initial drop at low strains. This behavior is attributed to the much reduced mobility of the branched CNTs and the lack of formation of crystalline structures around the bCNTs.
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    Robust homoclinic orbits in planar systems with Preisach hysteresis operator
    (Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2014) Pimenov, Alexander; Rachinskii, Dmitrii
    We construct examples of robust homoclinic orbits for systems of ordinary differential equations coupled with the Preisach hysteresis operator. Existence of such orbits is demonstrated for the first time. We discuss a generic mechanism that creates robust homoclinic orbits and a method for finding them. An example of a homoclinic orbit in a population dynamics model with hysteretic response of the prey to variations of the predator is studied numerically.