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See detailPlurilingual Identitites. On the way to an integrative view on language education?
Hu, Adelheid UL

in Bonnet, Andreas; Siemund, Peter (Eds.) Foreign Language Education in Multilingual Classrooms (2018)

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See detail"Kinder besitzen eine eigene Kraft für gute Lösungen". Zur Adressierung von Kindern im frühpädagogischen Partizipationsdiskurs
Hekel, Nicole UL

in Bloch, Bianca; Cloos, Peter; Schulz, Marc (Eds.) et al Kinder und Kindheit(en). Frühpädagogische Perspektiven (2018)

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See detailA Methodological Framework to Design a Machine-Readable Privacy Icon Set
Palmirani, Monica; Rossi, Arianna UL; Martoni, Michele et al

in Schweighofer, Erich (Ed.) Data Protection / LegalTech Proceedings of the 21st International Legal Informatics Symposium IRIS 2018 (2018)

The GDPR suggests icons to convey data practices in a more straightforward way. Although vi- sualizations to represent legal terms have many benefits, there is fear that they could be misrep- resented by ... [more ▼]

The GDPR suggests icons to convey data practices in a more straightforward way. Although vi- sualizations to represent legal terms have many benefits, there is fear that they could be misrep- resented by designers and misinterpreted by individuals, thus hindering instead of facilitating the comprehension. In order to solve these issues, we present a methodology to generate legal visual representations that is based on an analysis of legal requirements, on an ontological representation of the legal knowledge, and on an iterative, multi-stakeholder design approach, followed by empirical evaluation. [less ▲]

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See detailElliptic Curves Discrete Logarithm Problem over a Finite Field Fp and p-adic Approximations
Leprévost, Franck UL; Bernard, Nicolas UL; Bouvry, Pascal UL

in Proceedings of the 3rd International Conference on Applications in Information Technology (ICAIT-2018) (2018)

These notes summarize some computations conducted around the Elliptic Curves Discrete Logarithm Problem (ECDLP) over a finite field Fp.

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See detailThe University of Luxembourg: A National Excellence Initiative
Leprévost, Franck UL

in Altbach, Phil; Reisberg, Liz; Salmi, Jamil (Eds.) et al Accelerated Universities: A ideas and Money Combine to Build Academic Excellence (2018)

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See detailJames Bond's Most Secret Weapon
Leprévost, Franck UL

in Proceedings of the 3rd International Conference on Applications in Information Technology (2018)

This conference presents in a non-conventional way secret-key and public-key cryptology from its origins to the present days.

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See detailEditionsphilologie und inszenierende Typographie: eine praxeologische Perspektive auf die 'Mein-Kampf'-Edition des Instituts für Zeitgeschichte
Busch, Christopher UL; Ahrens, Moritz

in Editio : Internationales Jahrbuch für Editionswissenschaft = International Yearbook of Textual Criticism and Editorial Science] (2018), 32

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See detailClassification of red blood cell shapes in flow using outlier tolerant machine learning
Kihm, A.; Kaestner, L.; Wagner, Christian UL et al

in PLoS Computational Biology (2018)

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See detailAntimargination of microparticles and platelets in the vicinity of branching vessels
Bächer, C.; Kihm, A.; Schrack, L. et al

in Biophysical Journal (2018)

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See detailMining Fix Patterns for FindBugs Violations
Liu, Kui UL; Kim, Dongsun; Bissyande, Tegawendé François D Assise UL et al

in IEEE Transactions on Software Engineering (2018)

Several static analysis tools, such as Splint or FindBugs, have been proposed to the software development community to help detect security vulnerabilities or bad programming practices. However, the ... [more ▼]

Several static analysis tools, such as Splint or FindBugs, have been proposed to the software development community to help detect security vulnerabilities or bad programming practices. However, the adoption of these tools is hindered by their high false positive rates. If the false positive rate is too high, developers may get acclimated to violation reports from these tools, causing concrete and severe bugs being overlooked. Fortunately, some violations are actually addressed and resolved by developers. We claim that those violations that are recurrently fixed are likely to be true positives, and an automated approach can learn to repair similar unseen violations. However, there is lack of a systematic way to investigate the distributions on existing violations and fixed ones in the wild, that can provide insights into prioritizing violations for developers, and an effective way to mine code and fix patterns which can help developers easily understand the reasons of leading violations and how to fix them. In this paper, we first collect and track a large number of fixed and unfixed violations across revisions of software. The empirical analyses reveal that there are discrepancies in the distributions of violations that are detected and those that are fixed, in terms of occurrences, spread and categories, which can provide insights into prioritizing violations. To automatically identify patterns in violations and their fixes, we propose an approach that utilizes convolutional neural networks to learn features and clustering to regroup similar instances. We then evaluate the usefulness of the identified fix patterns by applying them to unfixed violations. The results show that developers will accept and merge a majority (69/116) of fixes generated from the inferred fix patterns. It is also noteworthy that the yielded patterns are applicable to four real bugs in the Defects4J major benchmark for software testing and automated repair. [less ▲]

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See detailDeep neural network with high-order neuron for the prediction of foamed concrete strength
Nguyen, Tuan; Kashani, Alireza; Ngo, Tuan et al

in Computer-Aided Civil and Infrastructure Engineering (2018)

The article presents a deep neural network model for the prediction of the compressive strength of foamed concrete. A new, high-order neuron was developed for the deep neural network model to improve the ... [more ▼]

The article presents a deep neural network model for the prediction of the compressive strength of foamed concrete. A new, high-order neuron was developed for the deep neural network model to improve the performance of the model. Moreover, the cross-entropy cost function and rectified linear unit activation function were employed to enhance the performance of the model. The present model was then applied to predict the compressive strength of foamed concrete through a given data set, and the obtained results were compared with other machine learning methods including conventional artificial neural network (C-ANN) and second-order artificial neural network (SO-ANN). To further validate the proposed model, a new data set from the laboratory and a given data set of high-performance concrete were used to obtain a higher degree of confidence in the prediction. It is shown that the proposed model obtained a better prediction, compared to other methods. In contrast to C-ANN and SO-ANN, the proposed model can genuinely improve its performance when training a deep neural network model with multiple hidden layers. A sensitivity analysis was conducted to investigate the effects of the input variables on the compressive strength. The results indicated that the compressive strength of foamed concrete is greatly affected by density, followed by the water-to-cement and sand-to-cement ratios. By providing a reliable prediction tool, the proposed model can aid researchers and engineers in mixture design optimization of foamed concrete. [less ▲]

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See detailNumerical–experimental observation of shape bistability of red blood cells flowing in a microchannel
Guckenberger, A.; Kihm, A.; John, T. et al

in European Physical Journal E. Soft Matter (2018)

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See detailTowards Purposeful Enterprise Modeling for Enterprise Analysis
de Kinderen, Sybren; Ma, Qin UL

in 2018 International Conference on Information Management & Management Science (2018)

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See detailDecomposing Models through Dependency Graphs
Ma, Qin UL; Kelsen, Pierre UL

in 12th International Symposium on Theoretical Aspects of Software Engineering (2018)

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See detailModeling in Support of Multi-Perspective Valuation of Smart Grid Initiatives
Kaczmarek-Heß, Monika; de Kinderen, Sybren; Ma, Qin UL et al

in IEEE 12th International Conference on Research Challenges in Information Science (2018)

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See detailEnabling Value Co-Creation in Customer Journeys with VIVA
Razo-Zapata, Iván; Chew, Eng; Ma, Qin UL et al

in Joint International Conference of Service Science and Innovation and Serviceology (2018)

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See detailKrichever-Novikov type algebras. Definitions and Results
Schlichenmaier, Martin UL

E-print/Working paper (2018)

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See detailHow does it feel to be a Third Country - Considerations on Brexit for Financial Services
Zetzsche, Dirk Andreas UL; Lehmann, M.

in Complexity's Embrace: The International Law Implications of Brexit (2018)

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See detailPersonalized risk prediction of postoperative cognitive impairment - rationale for the EU-funded BioCog project.
Winterer, G.; Androsova, Ganna UL; Bender, O. et al

in European psychiatry : the journal of the Association of European Psychiatrists (2018), 50

Postoperative cognitive impairment is among the most common medical complications associated with surgical interventions - particularly in elderly patients. In our aging society, it is an urgent medical ... [more ▼]

Postoperative cognitive impairment is among the most common medical complications associated with surgical interventions - particularly in elderly patients. In our aging society, it is an urgent medical need to determine preoperative individual risk prediction to allow more accurate cost-benefit decisions prior to elective surgeries. So far, risk prediction is mainly based on clinical parameters. However, these parameters only give a rough estimate of the individual risk. At present, there are no molecular or neuroimaging biomarkers available to improve risk prediction and little is known about the etiology and pathophysiology of this clinical condition. In this short review, we summarize the current state of knowledge and briefly present the recently started BioCog project (Biomarker Development for Postoperative Cognitive Impairment in the Elderly), which is funded by the European Union. It is the goal of this research and development (R&D) project, which involves academic and industry partners throughout Europe, to deliver a multivariate algorithm based on clinical assessments as well as molecular and neuroimaging biomarkers to overcome the currently unsatisfying situation. [less ▲]

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See detailDextran adsorption onto red blood cells revisited: single cell quantification by laser tweezers combined with microfluidics
Lee, K.; Shirshin, E.; Rovnyagina, N. et al

in Biomedical Optics Express (2018)

Detailed reference viewed: 48 (0 UL)