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End date: 2021 × Start date: 2020 × DDC: 004 × DDC: 620 × Type: Text ×

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    Steps towards a Dislocation Ontology for Crystalline Materials
    (Aachen, Germany : RWTH Aachen, 2021) Ihsan, Ahmad Zainul; Dessì, Danilo; Alam, Mehwish; Sack, Harald; Sandfeld, Stefan; García-Castro, Raúl; Davies, John; Antoniou, Grigoris; Fortuna, Carolina
    The field of Materials Science is concerned with, e.g., properties and performance of materials. An important class of materials are crystalline materials that usually contain “dislocations" - a line-like defect type. Dislocation decisively determine many important materials properties. Over the past decades, significant effort was put into understanding dislocation behavior across different length scales both with experimental characterization techniques as well as with simulations. However, for describing such dislocation structures there is still a lack of a common standard to represent and to connect dislocation domain knowledge across different but related communities. An ontology offers a common foundation to enable knowledge representation and data interoperability, which are important components to establish a “digital twin". This paper outlines the first steps towards the design of an ontology in the dislocation domain and shows a connection with the already existing ontologies in the materials science and engineering domain.
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    Ontology Modelling for Materials Science Experiments
    (Aachen, Germany : RWTH Aachen, 2021) Alam, Mehwish; Birkholz, Henk; Dessì, Danilo; Eberl, Christoph; Fliegl, Heike; Gumbsch, Peter; von Hartrott, Philipp; Mädler, Lutz; Niebel, Markus; Sack, Harald; Thomas, Akhil; Tiddi, Ilaria; Maleshkova, Maria; Pellegrini, Tassilo; de Boer, Victor
    Materials are either enabler or bottleneck for the vast majority of technological innovations. The digitization of materials and processes is mandatory to create live production environments which represent physical entities and their aggregations and thus allow to represent, share, and understand materials changes. However, a common standard formalization for materials knowledge in the form of taxonomies, ontologies, or knowledge graphs has not been achieved yet. This paper sketches the e_orts in modelling an ontology prototype to describe Materials Science experiments. It describes what is expected from the ontology by introducing a use case where a process chain driven by the ontology enables the curation and understanding of experiments.
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    Synchronization in 5G networks: a hybrid Bayesian approach toward clock offset/skew estimation and its impact on localization
    (Heidelberg : Springer, 2021) Goodarzi, Meysam; Cvetkovski, Darko; Maletic, Nebojsa; Gutiérrez, Jesús; Grass, Eckhard
    Clock synchronization has always been a major challenge when designing wireless networks. This work focuses on tackling the time synchronization problem in 5G networks by adopting a hybrid Bayesian approach for clock offset and skew estimation. Furthermore, we provide an in-depth analysis of the impact of the proposed approach on a synchronization-sensitive service, i.e., localization. Specifically, we expose the substantial benefit of belief propagation (BP) running on factor graphs (FGs) in achieving precise network-wide synchronization. Moreover, we take advantage of Bayesian recursive filtering (BRF) to mitigate the time-stamping error in pairwise synchronization. Finally, we reveal the merit of hybrid synchronization by dividing a large-scale network into local synchronization domains and applying the most suitable synchronization algorithm (BP- or BRF-based) on each domain. The performance of the hybrid approach is then evaluated in terms of the root mean square errors (RMSEs) of the clock offset, clock skew, and the position estimation. According to the simulations, in spite of the simplifications in the hybrid approach, RMSEs of clock offset, clock skew, and position estimation remain below 10 ns, 1 ppm, and 1.5 m, respectively.