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Now showing 1 - 10 of 179
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    Biobank Oversight and Sanctions Under the General Data Protection Regulation
    (Dordrecht ; Heidelberg ; New York ; London : Springer, 2021) Hallinan, Dara; Slokenberga, Santa; Tzortzatou, Olga; Reichel, Jane
    This contribution offers an insight into the function and problems of the oversight and sanctions mechanisms outlined in the General Data Protection Regulation as they relate to the biobanking context. These mechanisms might be considered as meta-mechanisms—mechanisms relating to, but not consisting of, substantive legal principles—functioning in tandem to ensure biobank compliance with data protection principles. Each of the mechanisms outlines, on paper at least, comprehensive and impressive compliance architecture—both expanding on their capacity in relation to Directive 95/46. Accordingly, each mechanism looks likely to have a significant and lasting impact on biobanks and biobanking. Despite this comprehensiveness, however, the mechanisms are not immune from critique. Problems appear regarding the standard of protection provided for research subject rights, regarding the disproportionate impact on legitimate interests tied up with the biobanking process—particularly genomic research interests—and regarding their practical implementability in biobanking.
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    A Review on Recent Advances in Video-based Learning Research: Video Features, Interaction, Tools, and Technologies
    (Aachen, Germany : RWTH Aachen, 2021) Navarrete, Evelyn; Hoppe, Anett; Ewerth, Ralph; Cong, Gao; Ramanath, Maya
    Human learning shifts stronger than ever towards online settings, and especially towards video platforms. There is an abundance of tutorials and lectures covering diverse topics, from fixing a bike to particle physics. While it is advantageous that learning resources are freely available on the Web, the quality of the resources varies a lot. Given the number of available videos, users need algorithmic support in finding helpful and entertaining learning resources. In this paper, we present a review of the recent research literature (2020-2021) on video-based learning. We focus on publications that examine the characteristics of video content, analyze frequently used features and technologies, and, finally, derive conclusions on trends and possible future research directions.
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    Saltwater intrusion under climate change in North-Western Germany - mapping, modelling and management approaches in the projects TOPSOIL and go-CAM
    (Les Ulis : EDP Sciences, 2018) Wiederhold, Helga; Scheer, Wolfgang; Kirsch, Reinhard; Azizur Rahman, M.; Ronczka, Mathias; Szymkiewicz, Adam; Sadurski, A.; Jaworska-Szulc, B.
    Climate change will result in rising sea level and, at least for the North Sea region, in rising groundwater table. This leads to a new balance at the fresh–saline groundwater boundary and a new distribution of saltwater intrusions with strong regional differentiations. These effects are investigated in several research projects funded by the European Union and the German Federal Ministry of Education and Research (BMBF). Objectives and some results from the projects TOPSOIL and go-CAM are presented in this poster.
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    A Case for Integrated Data Processing in Large-Scale Cyber-Physical Systems
    (Maui, Hawaii : HICSS, 2019) Glebke, René; Henze, Martin; Wehrle, Klaus; Niemietz, Philipp; Trauth, Daniel; Mattfeld, Patrick; Bergs, Thomas; Bui, Tung X.
    Large-scale cyber-physical systems such as manufacturing lines generate vast amounts of data to guarantee precise control of their machinery. Visions such as the Industrial Internet of Things aim at making this data available also to computation systems outside the lines to increase productivity and product quality. However, rising amounts and complexities of data and control decisions push existing infrastructure for data transmission, storage, and processing to its limits. In this paper, we exemplarily study a fine blanking line which can produce up to 6.2 Gbit/s worth of data to showcase the extreme requirements found in modern manufacturing. We consequently propose integrated data processing which keeps inherently local and small-scale tasks close to the processes while at the same time centralizing tasks relying on more complex decision procedures and remote data sources. Our approach thus allows for both maintaining control of field-level processes and leveraging the benefits of “big data” applications.
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    Formalizing Gremlin pattern matching traversals in an integrated graph Algebra
    (Aachen, Germany : RWTH Aachen, 2019) Thakkar, Harsh; Auer, Sören; Vidal, Maria-Esther; Samavi, Reza; Consens, Mariano P.; Khatchadourian, Shahan; Nguyen, Vinh; Sheth, Amit; Giménez-García, José M.; Thakkar, Harsh
    Graph data management (also called NoSQL) has revealed beneficial characteristics in terms of flexibility and scalability by differ-ently balancing between query expressivity and schema flexibility. This peculiar advantage has resulted into an unforeseen race of developing new task-specific graph systems, query languages and data models, such as property graphs, key-value, wide column, resource description framework (RDF), etc. Present-day graph query languages are focused towards flex-ible graph pattern matching (aka sub-graph matching), whereas graph computing frameworks aim towards providing fast parallel (distributed) execution of instructions. The consequence of this rapid growth in the variety of graph-based data management systems has resulted in a lack of standardization. Gremlin, a graph traversal language, and machine provide a common platform for supporting any graph computing sys-tem (such as an OLTP graph database or OLAP graph processors). In this extended report, we present a formalization of graph pattern match-ing for Gremlin queries. We also study, discuss and consolidate various existing graph algebra operators into an integrated graph algebra.
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    Fingertip friction and tactile rating of wrapping papers
    (Berlin ; Heidelberg : Springer, 2022) Jost, Kim Michèle; Drewing, Knut; Bennewitz, Roland; Seifi, Hasti; Kappers, Astrid M. L.; Schneider, Oliver; Drewing, Knut; Pacchierotti, Claudio; Abbasimoshaei, Alireza; Huisman, Gijs; Kern, Thorsten A.
    The tactile exploration and perception of wrapping papers is investigated in terms of fingertip friction and rating of sensory, affective, and evaluative adjectives. Friction coefficients, which vary significantly between samples, are correlated with factors such as valence which are identified in a principal component analysis of subjective ratings. We found that affective appraisals of valence and arousal as well as evaluations of novelty, but not of value, decreased with increasing friction.
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    On the Role of Images for Analyzing Claims in Social Media
    (Aachen, Germany : RWTH Aachen, 2021) Cheema, Gullal S.; Hakimov, Sherzod; Müller-Budack, Eric; Ewerth, Ralph
    Fake news is a severe problem in social media. In this paper, we present an empirical study on visual, textual, and multimodal models for the tasks of claim, claim check-worthiness, and conspiracy detection, all of which are related to fake news detection. Recent work suggests that images are more influential than text and often appear alongside fake text. To this end, several multimodal models have been proposed in recent years that use images along with text to detect fake news on social media sites like Twitter. However, the role of images is not well understood for claim detection, specifically using transformer-based textual and multimodal models. We investigate state-of-the-art models for images, text (Transformer-based), and multimodal information for four different datasets across two languages to understand the role of images in the task of claim and conspiracy detection.
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    Measurements of particle backscatter, extinction, and lidar ratio at 1064 nm with the rotational raman method in Polly-XT
    (Les Ulis : EDP Sciences, 2018) Engelmann, Ronny; Haarig, Moritz; Baars, Holger; Ansmann, Albert; Kottas, Michael; Marinou, Eleni; Nicolae, D.; Makoto, A.; Vassilis, A.; Balis, D.; Behrendt, A.; Comeron, A.; Gibert, F.; Landulfo, E.; McCormick, M.P.; Senff, C.; Veselovskii, I.; Wandinger, U.
    We replaced a 1064-nm interference filter of a Polly-XT lidar system by a 1058-nm filter to observe pure rotational Raman backscattering from atmospheric Nitrogen and Oxygen. Polly-XT is compact Raman lidar with a Nd:YAG laser (20 Hz, 200 mJ at 1064 nm) and a 30-cm telescope mirror which applies photomultipliers in photoncounting mode. We present the first measured signals at 1058 nm and the derived extinction profile from measurements aboard RV Polarstern and in Leipzig. In combination with another Polly-XT system we could also derive particle backscatter and lidar ratio profiles at 1064 nm.
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    Survey on Big Data Applications
    (Cham : Springer, 2020) Janev, Valentina; Pujić, Dea; Jelić, Marko; Vidal, Maria-Esther; Janev, Valentina; Graux, Damien; Jabeen, Hajira; Sallinger, Emanuel
    The goal of this chapter is to shed light on different types of big data applications needed in various industries including healthcare, transportation, energy, banking and insurance, digital media and e-commerce, environment, safety and security, telecommunications, and manufacturing. In response to the problems of analyzing large-scale data, different tools, techniques, and technologies have bee developed and are available for experimentation. In our analysis, we focused on literature (review articles) accessible via the Elsevier ScienceDirect service and the Springer Link service from more recent years, mainly from the last two decades. For the selected industries, this chapter also discusses challenges that can be addressed and overcome using the semantic processing approaches and knowledge reasoning approaches discussed in this book.
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    Understanding Class Representations: An Intrinsic Evaluation of Zero-Shot Text Classification
    (Aachen, Germany : RWTH Aachen, 2021) Hoppe, Fabian; Dessì, Danilo; Sack, Harald; Alam, Mehwish; Buscaldi, Davide; Cochez, Michael; Osborne, Francesco; Reforgiato Recupero, Diego; Sack, Harald
    Frequently, Text Classification is limited by insufficient training data. This problem is addressed by Zero-Shot Classification through the inclusion of external class definitions and then exploiting the relations between classes seen during training and unseen classes (Zero-shot). However, it requires a class embedding space capable of accurately representing the semantic relatedness between classes. This work defines an intrinsic evaluation based on greater-than constraints to provide a better understanding of this relatedness. The results imply that textual embeddings are able to capture more semantics than Knowledge Graph embeddings, but combining both modalities yields the best performance.