@article{22541, abstract = {{Monodisperse micron-sized silica particle monolayers deposited onto plasma-grown SiOx-ultra-thin films have been used as reference systems to investigate wetting, water adsorption and capillary bridge formation as a function of silica surface functionalization. 1H,1H, 2H,2H perfluorooctyltriethoxysil (FOTS) monolayers, have been deposited on the respective surfaces by means of chemical vapor deposition resulting in macroscopically low energy surfaces. X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared (FTIR) reflection absorption spectroscopy confirmed the monolayer formation. Water adsorption isotherms were studied by a combination of in-situ FTIR reflection spectroscopy and quartz crystal microbalance (QCM) while macroscopic wetting was analysed by contact angle measurements. The comparative data evaluation indicates that the macroscopic wetting behaviour was changed as expected, however, that water nanodroplets formed both at intrinsic defects of the FOTS monolayer and at the FOTS/SiOx interface. Capillary bridges of liquid water are dominantly formed in the confined particle contact areas and between surface asperities on the particles. The comparison of wetting, adsorption and capillary bridge formation shows that the hydrophobization of porous materials by organosilane monolayers leads to the formation of morphology dependent nanoscopic defects that act as sites for preferential capillary bridge formation.}}, author = {{Giner, Ignacio and Torun, Boray and Han, Yan and Duderija, Belma and Meinderink, Dennis and Orive, Alejandro González and de los Arcos de Pedro, Maria Teresa and Weinberger, Christian and Tiemann, Michael and Schmid, Hans-Joachim and Grundmeier, Guido}}, issn = {{0169-4332}}, journal = {{Applied Surface Science}}, pages = {{873--879}}, title = {{{Water adsorption and capillary bridge formation on silica micro-particle layers modified with perfluorinated organosilane monolayers}}}, doi = {{10.1016/j.apsusc.2018.12.221}}, year = {{2019}}, } @article{43019, author = {{Schmidt, H.C. and Homberg, W. and Orive, A.G. and Grundmeier, G. and Duderija, B. and Hordych, I. and Herbst, S. and Nürnberger, F. and Maier, H.J.}}, issn = {{0933-5137}}, journal = {{Materialwissenschaft und Werkstofftechnik}}, keywords = {{Mechanical Engineering, Mechanics of Materials, Condensed Matter Physics, General Materials Science}}, number = {{8}}, pages = {{924--939}}, publisher = {{Wiley}}, title = {{{Joining of blanks by cold pressure welding: Incremental rolling and strategies for surface activation and heat treatment}}}, doi = {{10.1002/mawe.201900031}}, volume = {{50}}, year = {{2019}}, } @misc{14903, author = {{Asenkerschbaumer, Stefan and Sureth-Sloane, Caren}}, booktitle = {{Frankfurter Allgemeine Zeitung}}, number = {{209}}, pages = {{18}}, title = {{{Aus Daten müssen Informationen werden}}}, year = {{2019}}, } @inbook{46153, abstract = {{Since its beginnings in the late 1980s, the field of Learner Corpus Research (LCR) has been continuously evolving and thereby widening its scope. LCR is rapidly closing gaps within its original scope by expanding on the languages, language mediums (spoken vs written) and learner types covered, and it is turning its attention to ever-emerging new research questions and phenomena which arise at the crossroads with neighboring disciplines. In fact, by embracing e.g. the latest technical developments in Natural Language Processing and Computer Science as well as by adopting state-of-the-art research methodologies used in Corpus Linguistics which include sophisticated statistical methods of data analysis, LCR is dipping into new interdisciplinary subjects with curiosity and expanding its research scope and methodological repertoire. This volume combines selected research papers from the 4th LCR conference hosted by Eurac Research in Bolzano/Bozen (Italy) in October 2017. All contributions in this volume build on the topics of previous LCR conference volumes, and enrich them with their research. The contributions are arranged thematically and refer to the following ve LCR topics: (1) analysis of learner data in spoken language, (2) analysis of learner data in corpora of other languages than English, (3) analysis of learner data of young learners, (4) LCR, language learning and pedagogical applications, and (5) LCR and automatic language modeling. The assembled papers introduce innovative research strands, present original data and research findings, and discuss latest desiderata within the five thematic focal points of the book.}}, author = {{Weber, Tassja}}, booktitle = {{ Widening the Scope of Learner Corpus Research. Selected papers from the fourth Learner Corpus Research Conference.}}, editor = {{Abel, Andrea and Glaznieks, Aivars and Lyding, Verena and Nicolas, Lionel}}, isbn = {{2875588699}}, pages = {{121--136}}, publisher = {{Presses universitaires de Louvain}}, title = {{{A corpus-based approach to the usage and acquisition of prepositions by learners of German as a foreign language: form vs. function.}}}, year = {{2019}}, } @misc{45836, author = {{Kostan, Anastassija}}, booktitle = {{Verwandtschaftsverhältnisse – Geschlechterverhältnisse im 21. Jahrhundert}}, issn = {{2196-4467}}, number = {{2-2019}}, pages = {{163--165}}, publisher = {{Verlag Barbara Budrich GmbH}}, title = {{{Imke Leicht/Christine Löw/Nadja Meisterhans/Katharina Volk (Hrsg.), 2017: Material turn: Feministische Perspektiven auf Materialität und Materialismus. Opladen, Berlin, Toronto: Verlag Barbara Budrich. 205 Seiten. 29,90 Euro}}}, doi = {{10.3224/gender.v11i2.13}}, volume = {{11}}, year = {{2019}}, } @misc{15874, author = {{Lienen, Christian}}, publisher = {{Universität Paderborn}}, title = {{{Implementing a Real-time System on a Platform FPGA operated with ReconOS}}}, year = {{2019}}, } @article{16312, author = {{Steube, Jakob and Burkhardt, Lukas and Päpcke, Ayla and Moll, Johannes and Zimmer, Peter and Schoch, Roland and Wölper, Christoph and Heinze, Katja and Lochbrunner, Stefan and Bauer, Matthias}}, issn = {{0947-6539}}, journal = {{Chemistry – A European Journal}}, pages = {{11826--11830}}, title = {{{Excited‐State Kinetics of an Air‐Stable Cyclometalated Iron(II) Complex}}}, doi = {{10.1002/chem.201902488}}, year = {{2019}}, } @inproceedings{29037, abstract = {{Existing technologies employ different machine learning approaches to predict disasters from historical environmental data. However, for short-term disasters (e.g., earthquakes), historical data alone has a limited prediction capability. In this work, we consider social media as a supplementary source of knowledge in addition to historical environmental data. Further, we build a joint model that learns from disaster-related tweets and environmental data to improve prediction. We propose the combination of semantically-enriched word embedding to represent entities in tweets with their semantics representations computed with the traditional word2vec. Our experiments show that our proposed approach outperforms the accuracy of state-of-the-art models in disaster prediction.}}, author = {{Zahera, Hamada Mohamed Abdelsamee and Sherif, Mohamed and Ngonga Ngomo, Axel-Cyrille}}, booktitle = {{K-CAP 2019: Knowledge Capture Conference}}, keywords = {{sys:relevantFor:infai sys:relevantFor:bis sys:relevantFor:simba ngonga simba zahera sherif solide limboproject opal group\_aksw dice}}, pages = {{4}}, title = {{{Jointly Learning from Social Media and Environmental Data for Typhoon Intensity Prediction}}}, year = {{2019}}, } @inproceedings{29011, abstract = {{In this paper we present LimesWebUI, our web interface of Limes. Limes, the Link Discovery Framework for Metric Spaces, is a framework for dis- covering links between entities contained in Linked Data sources. LimesWebUI assists the end user during the link discovery process. By representing the link specifications (LS) as interlocking blocks, our interface eases the manual creation of links for users who already know which LS they would like to execute. How- ever, most users do not know which LS suits their linking task best and therefore need help throughout this process. Hence, our interface provides wizards which allow the easy configuration of many link discovery machine learning algorithms, that does not require the user to enter a manual LS. We evaluate the usability of the interface by using the standard system usability scale questionnaire. Our over- all usability score of 76.5 suggests that the online interface is consistent, easy to use, and the various functions of the system are well integrated.}}, author = {{Sherif, Mohamed and Pestryakova, Svetlana and Dreßler, Kevin and Ngonga Ngomo, Axel-Cyrille}}, booktitle = {{18th International Semantic Web Conference (ISWC 2019)}}, keywords = {{2019 sys:relevantFor:infai group\_aksw simba sherif kevin ngonga Svetlana slipo limes dice sage limbo opal}}, publisher = {{CEUR-WS.org}}, title = {{{LimesWebUI – Link Discovery Made Simple}}}, year = {{2019}}, } @inproceedings{29003, abstract = {{In this paper, we describe our approach to classify disaster-related tweets into multilabel information types (ie, labels). We aim to filter first relevant tweets during disasters. Then, we assign tweets relevant information types. Information types can be SearchAndRescue, MovePeople and Volunteer. We employ a fine-tuned BERT model with 10 BERT layers. Further, we submitted our approach to the TREC-IS 2019 challenge, the evaluation results showed that our approach outperforms the F1-score of median score in identifying actionable information.}}, author = {{Zahera, Hamada Mohamed Abdelsamee and A. Elgendy, Ibrahim and Jalota, Rricha and Sherif, Mohamed}}, booktitle = {{Proceedings of the Twenty-Eighth Text REtrieval Conference, {TREC} 2019, Gaithersburg, Maryland, USA, November 13-15, 2019}}, keywords = {{zahera elgendy jalota sherif dice}}, title = {{{Fine-tuned BERT Model for Multi-Label Tweets Classification}}}, year = {{2019}}, } @inproceedings{29038, abstract = {{An increasing number of heterogeneous datasets abiding by the Linked Data paradigm is published everyday. Discovering links between these datasets is thus central to achieving the vision behind the Data Web. Declarative Link Discovery (LD) frameworks rely on complex Link Specification (LS) to express the conditions under which two resources should be linked. Complex LS combine similarity measures with thresholds to determine whether a given predicate holds between two resources. State of the art LD frameworks rely mostly on string-based similarity measures such as Levenshtein and Jaccard. However, string-based similarity measures often fail to catch the similarity of resources with phonetically similar property values when these property values are represented using different string representation (e.g., names and street labels). In this paper, we evaluate the impact of using phonetics-based similarities in the process of LD. Moreover, we evaluate the impact of phonetic-based similarity measures on a state-of-the-art machine learning approach used to generate LS. Our experiments suggest that the combination of string-based and phonetic-based measures can improve the Fmeasures achieved by LD frameworks on most datasets.}}, author = {{Ahmed, Abdullah Fathi Ahmed and Sherif, Mohamed and Ngonga Ngomo, Axel-Cyrille}}, booktitle = {{K-CAP 2019: Knowledge Capture Conference}}, keywords = {{sys:relevantFor:infai sys:relevantFor:bis sys:relevantFor:ngonga ahmed sherif solide limboproject opal group_aksw dice}}, title = {{{Do your Resources Sound Similar? On the Impact of Using Phonetic Similarity in Link Discovery}}}, year = {{2019}}, } @inproceedings{29012, abstract = {{An increasing number and size of datasets abiding by the Linked Data paradigm are published everyday. Discovering links between these datasets is thus central to achieve the vision behind the Data Web. Declarative Link Discovery (LD) frameworks rely on complex Link Specification (LS) to express the conditions under which two resources should be linked. Understanding such LS is not a trivial task for non-expert users, particularly when such users are interested in generating LS to match their needs. Even if the user applies a machine learning algorithm for the automatic generation of the required LS, the challenge of explaining the resultant LS persists. Hence, providing explainable LS is the key challenge to enable users who are unfamiliar with underlying LS technologies to use them effectively and efficiently. In this paper, we address this problem by proposing a generic approach that allows a LS to be verbalized, i.e., converted into understandable natural language. We propose a summarization approach to the verbalized LS based on the selectivity of the underlying LS. Our adequacy and fluency evaluations show that our approach can generate complete and easily understandable natural language descriptions even by lay users.}}, author = {{Fathi Ahmed, Abdullah and Sherif, Mohamed and Ngonga Ngomo, Axel-Cyrille}}, booktitle = {{24th International Conference on Applications of Natural Language to Information Systems (NLDB 2019)}}, keywords = {{2019 sys:relevantFor:infai group\_aksw simba sherif ngonga ahmed slipo limes dice sage limbo opal}}, publisher = {{Springer}}, title = {{{LSVS: Link Specification Verbalization and Summarization}}}, year = {{2019}}, } @inproceedings{29013, abstract = {{Point of Interest (POI) data constitute the cornerstone of any application, service or product even remotely related to our physical surroundings. From navigation applications to social networks, tourism, and logistics, we use POI data to search, communicate, decide and plan our actions. POIs are semantically diverse and spatio-temporally evolving entities, having geographical, temporal and thematic relations. Currently, integrating POI data to increase their coverage, timeliness, accuracy and value is a resource-intensive and mostly manual process, with no specialized software available to address the specific challenges of this task. In this paper, we present an integrated toolkit for transforming, linking, fusing and enriching POI data, and extracting additional value from them. In particular, we demonstrate how Linked Data technologies can address the limitations, gaps and challenges of the current landscape in Big POI data integration. We have built a prototype application that enables users to define, manage and execute scalable POI data integration workflows built on top of state-of-the-art software for geospatial Linked Data. The application abstracts and hides away the underlying complexity, automates quality-assured integration, scales efficiently for world-scale integration tasks and lowers the entry barrier for end-users. Validated against real-world POI datasets in several application domains, our system has shown great potential to address the requirements and needs of cross-sector, cross-border and cross-lingual integration of Big POI data.}}, author = {{Athanasiou, Spiros and Giorgos, Giannopoulos and Damien, Graux and Nikos, Karagiannakis and Jens, Lehmann and Ngonga Ngomo, Axel-Cyrille and Kostas, Patroumpas and Sherif, Mohamed and Skoutas, Dimitrios}}, booktitle = {{International Conference on Extending Database Technology 2019, EDBT19}}, keywords = {{2019 sys:relevantFor:infai group\_aksw simba sherif ngonga lehmann slipo limes dice deer}}, title = {{{Big POI data integration with Linked Data technologies}}}, year = {{2019}}, } @article{15074, author = {{Kamhöfer, Daniel A and Schmitz, Hendrik and Westphal, Matthias}}, issn = {{1542-4766}}, journal = {{Journal of the European Economic Association}}, number = {{1}}, pages = {{205--244}}, title = {{{Heterogeneity in Marginal Non-Monetary Returns to Higher Education}}}, doi = {{10.1093/jeea/jvx058}}, volume = {{17}}, year = {{2019}}, } @article{46607, author = {{Schubert, Michael}}, journal = {{Journal of Borderlands Studies}}, pages = {{527 -- 545}}, title = {{{The Creation of Illegal Migration in the German Confederation, 1815–1866}}}, volume = {{34}}, year = {{2019}}, } @inproceedings{46675, author = {{Eggert, A. and Böhm, Eva and Akalan, R. and Gebauer, H.}}, booktitle = {{9th BMM-EMAC Biennial International Conference on Business Market Management, Berlin}}, location = {{Berlin}}, title = {{{Service growth by acquisition – An event study}}}, year = {{2019}}, } @misc{31355, booktitle = {{Veröffentlichungen der Universität Paderborn}}, editor = {{---, --}}, title = {{{„Die Flucht“ (1977) oder: Die wachsende Ratlosigkeit nach 1976}}}, year = {{2019}}, } @article{42673, abstract = {{The article analyzes how an emerging form of automation may drastically transform contemporary employment dynamics. Recent breakthroughs in the field of artificial intelligence (AI) make it possible to automate both manual and mental non-standard tasks. The first part of the article traces the development of AI. Whereas classical algorithms required the creation of a hermetic environment for AI to thrive, modern neural network-based AI is capable of surviving in the chaotic realm occupied by humans. Based on an analysis of changes in the nature of AI, the authors distinguish between substitutive and supplemental automation. The former refers to a complete replacement of humans by machines, while the latter indicates a selective substitution of humans in specific professional functions. In order to conceptualize professions as a nexus of automatable components, the authors employ Goffman’s dramaturgical framework. Goffman studied the social visibility of professional activity. Goffman held that any profession can be divided into invisible routines that are fundamental to it and a dramatization that makes the profession socially visible. The article demonstrates that the current utopian and antiutopian views of automation both reduce work to its visible components and neglect the logic of supplemental automation. The authors argue that the targets of modern automation are not the socially visible components but the invisible routines. In the final section, the authors develop a model that takes these invisible professional routines into account and analyze what effect this new type of automation may have on different types of professions with differing degrees of social visibility.}}, author = {{Klowait, Nils and Erofeeva, Maria}}, issn = {{2499-9628}}, journal = {{Philosophical Literary Journal Logos}}, keywords = {{Literature and Literary Theory, Philosophy, Cultural Studies}}, number = {{1}}, pages = {{53--84}}, publisher = {{The Russian Presidential Academy of National Economy and Public Administration}}, title = {{{Work in the Age of Intelligent Machines: The Rise of Invisible Automation}}}, doi = {{10.22394/0869-5377-2019-1-53-80}}, volume = {{29}}, year = {{2019}}, } @article{41339, author = {{Garnefeld, Ina and Eggert, Andreas and Husemann-Kopetzky, Markus and Böhm, Eva}}, issn = {{0092-0703}}, journal = {{Journal of the Academy of Marketing Science}}, keywords = {{Marketing, Economics and Econometrics, Business and International Management}}, number = {{4}}, pages = {{595--616}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Exploring the link between payment schemes and customer fraud: a mental accounting perspective}}}, doi = {{10.1007/s11747-019-00653-x}}, volume = {{47}}, year = {{2019}}, } @article{46803, abstract = {{ABSTRACTDrawing on the political theory of judicial decision making, our paper proposes a new and parsimonious ex ante litigation risk measure: federal judge ideology. We find that judge ideology complements existing measures of litigation risk based on industry membership and firm characteristics. Firms in liberal circuits (the third quartile in ideology) are 33.5% more likely to be sued in securities class action lawsuits than those in conservative circuits (the first quartile in ideology). This result is stronger after the U.S. Supreme Court's ruling in the Tellabs case. We next show that the effect of judge ideology on litigation risk is greater for firms with more sophisticated shareholders and with higher expected litigation costs. Furthermore, judicial appointments affect litigation risk and the value of firms in the circuit, highlighting the economic consequences of political appointments of judges. Finally, using our new measure, we document that litigation risk deters managers from providing long‐term earnings guidance, a result that existing measures of litigation risk cannot show.}}, author = {{HUANG, ALLEN and HUI, KAI WAI and Li, Reeyarn}}, issn = {{0021-8456}}, journal = {{Journal of Accounting Research}}, keywords = {{Economics and Econometrics, Finance, Accounting}}, number = {{2}}, pages = {{431--489}}, publisher = {{Wiley}}, title = {{{Federal Judge Ideology: A New Measure of Ex Ante Litigation Risk}}}, doi = {{10.1111/1475-679x.12260}}, volume = {{57}}, year = {{2019}}, }