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- ItemUnveiling 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, IsmailIndustry 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.
- ItemFigures in Scientific Open Access Publications(New York, NY : Springer, 2018) Sohmen, Lucia; Charbonnier, Jean; Blümel, Ina; Wartena, Christian; Heller, Lambert; Méndez, E.; Crestani, F.; Ribeiro, C.; David, G.; Lopes, J.This paper summarizes the results of a comprehensive statistical analysis on a corpus of open access articles and contained figures. It gives an insight into quantitative relationships between illustrations or types of illustrations, caption lengths, subjects, publishers, author affiliations, article citations and others.
- ItemQuestion Answering on Scholarly Knowledge Graphs(Cham : Springer, 2020) Jaradeh, Mohamad Yaser; Stocker, Markus; Auer, Sören; Hall, Mark; Merčun, Tanja; Risse, Thomas; Duchateau, FabienAnswering questions on scholarly knowledge comprising text and other artifacts is a vital part of any research life cycle. Querying scholarly knowledge and retrieving suitable answers is currently hardly possible due to the following primary reason: machine inactionable, ambiguous and unstructured content in publications. We present JarvisQA, a BERT based system to answer questions on tabular views of scholarly knowledge graphs. Such tables can be found in a variety of shapes in the scholarly literature (e.g., surveys, comparisons or results). Our system can retrieve direct answers to a variety of different questions asked on tabular data in articles. Furthermore, we present a preliminary dataset of related tables and a corresponding set of natural language questions. This dataset is used as a benchmark for our system and can be reused by others. Additionally, JarvisQA is evaluated on two datasets against other baselines and shows an improvement of two to three folds in performance compared to related methods.
- ItemOntology 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, FabienThe 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.
- ItemError estimates for nonlinear reaction-diffusion systems involving different diffusion length scales(Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2014) Reichelt, SinaWe derive quantitative error estimates for coupled reaction-diffusion systems, whose coefficient functions are quasi-periodically oscillating modeling microstructure of the underlying macroscopic domain. The coupling arises via nonlinear reaction terms, and we allow for different diffusion length scales, i.e. whereas some species have characteristic diffusion length of order 1, other species may diffuse much slower, namely, with order of the characteristic microstructure-length scale. We consider an effective system, which is rigorously obtained via two-scale convergence, and we prove that the error of its solution to the original solution is of order 1/2.
- ItemFunMap: Efficient Execution of Functional Mappings for Knowledge Graph Creation(Cham : Springer, 2020) Jozashoori, Samaneh; Chaves-Fraga, David; Iglesias, Enrique; Vidal, Maria-Esther; Corcho, Oscar; Pan, Jeff Z.; Tamma, Valentina; d'Amato, Claudia; Janowicz, Kryztof; Fu, Bo; Polleres, Axel; Seneviratne, Oshani; Kagal, LalanaData has exponentially grown in the last years, and knowledge graphs constitute powerful formalisms to integrate a myriad of existing data sources. Transformation functions – specified with function-based mapping languages like FunUL and RML+FnO – can be applied to overcome interoperability issues across heterogeneous data sources. However, the absence of engines to efficiently execute these mapping languages hinders their global adoption. We propose FunMap, an interpreter of function-based mapping languages; it relies on a set of lossless rewriting rules to push down and materialize the execution of functions in initial steps of knowledge graph creation. Although applicable to any function-based mapping language that supports joins between mapping rules, FunMap feasibility is shown on RML+FnO. FunMap reduces data redundancy, e.g., duplicates and unused attributes, and converts RML+FnO mappings into a set of equivalent rules executable on RML-compliant engines. We evaluate FunMap performance over real-world testbeds from the biomedical domain. The results indicate that FunMap reduces the execution time of RML-compliant engines by up to a factor of 18, furnishing, thus, a scalable solution for knowledge graph creation.
- ItemStoff-/Energiewandlung und Arbeitsleistung bei Verbrennungsmotoren : Thermodynamische und verbrennungstechnische Grundlagen(Hannover : Technische Informationsbibliothek, 2021) Kleinschmidt, WalterZu dem hier angesprochenen Fachgebiet existiert eine sehr umfangreiche Fachliteratur. Die vorliegende Schrift geht die Thematik aber in einer sehr eigenständigen kurzgefassten und prägnanten Weise an. Zudem sind Ausführungen und Gesichtspunkte enthalten, die der Verfasser bisher nicht an anderer Stelle gefunden hat. Der Text wurde aus Unterlagen des Verfassers zusammengestellt, die während seiner früheren Lehr- und Forschungstätigkeit an der Universität Siegen im damaligen Fachbereich Maschinentechnik, Lehrgebiet Energietechnik / Kolbenmaschinen entstanden sind.
- ItemHausdorff metric BV discontinuity of sweeping processes(Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2014) Klein, Olaf; Recupero, VincenzoSweeping processes are a class of evolution differential inclusions arising in elastoplasticity and were introduced by J.J. Moreau in the early seventies. The solution operator of the sweeping processes represents a relevant example of emphrate independent operator containing as a particular case the so called emphplay operator which is widely used in hysteresis. The continuity properties of these operators were studied in several works. In this note we address the continuity with respect to the strict metric in the space of functions of bounded variation with values in the metric space of closed convex subsets of a Hilbert space. We provide a counterexample showing that the solution operator of the sweeping process is not continuous when its domain is endowed with the strict topology of BV and its codomain is endowed with the L1-topology. This is at variance with the case of the play operator which instead is continuous in this sense.
- ItemMore specific signal detection in functional magnetic resonance imaging by false discovery rate control for hierarchically structured systems of hypotheses(Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2015) Schildknecht, Konstantin; Tabelow, Karsten; Dickhaus, ThorstenSignal detection in functional magnetic resonance imaging (fMRI) inherently involves the problem of testing a large number of hypotheses. A popular strategy to address this multiplicity is the control of the false discovery rate (FDR). In this work we consider the case where prior knowledge is available to partition the set of all hypotheses into disjoint subsets or families, e. g., by a-priori knowledge on the functionality of certain regions of interest. If the proportion of true null hypotheses differs between families, this structural information can be used to increase statistical power. We propose a two-stage multiple test procedure which first excludes those families from the analysis for which there is no strong evidence for containing true alternatives. We show control of the family-wise error rate at this first stage of testing. Then, at the second stage, we proceed to test the hypotheses within each non-excluded family and obtain asymptotic control of the FDR within each family in this second stage. Our main mathematical result is that this two-stage strategy implies asymptotic control of the FDR with respect to all hypotheses. In simulations we demonstrate the increased power of this new procedure in comparison with established procedures in situations with highly unbalanced families. Finally, we apply the proposed method to simulated and to real fMRI data.
- ItemExtruded polycarbonate/Di-Allyl phthalate composites with ternary conductive filler system for bipolar plates of polymer electrolyte membrane fuel cells(Bristol : IOP Publ., 2019) Naji, Ahmed; Krause, Beate; Pötschke, Petra; Ameli, AmirHere, we report multifunctional polycarbonate (PC)-based conductive polymer composites (CPCs) with outstanding performance manufactured by a simple extrusion process and intended for use in bipolar plate (BPP) applications in polymer electrolyte membrane (PEM) fuel cells. CPCs were developed using a ternary conductive filler system containing carbon nanotube (CNT), carbon fiber (CF), and graphite (G) and by introducing di-allyl phthalate (DAP) as a plasticizer to PC matrix. The samples were fabricated using twin-screw extrusion followed by compression molding and the microstructure, electrical conductivity, thermal conductivity, and mechanical properties were investigated. The results showed a good dispersion of the fillers with some degree of interconnection between dissimilar fillers. The addition of DAP enhanced the electrical conductivity and tensile strength of the CPCs. Due to its plasticizing effect, DAP reduced the processing temperature by 75 °C and facilitated the extrusion of CPCs with filler loads as high as 63 wt% (3 wt% CNT, 30 wt% CF, 30 wt% G). Consequently, CPCs with the through-plane electrical, in-plane electrical and thermal conductivities and tensile strength of 4.2 S cm-1, 34.3 S cm-1, 2.9 W m-1 K-1, and 75.4 MPa, respectively, were achieved. This combination of properties indicates the potential of PC-based composites enriched with hybrid fillers and plasticizers as an alternative material for BPP application.