306 research outputs found

    In situ growth regime characterization of cubic GaN using reflection high energy electron diffraction

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    Cubic GaN layers were grown by plasma-assisted molecular beam epitaxy on 3C-SiC (001)substrates. In situ reflection high energy electron diffraction was used to quantitatively determine the Ga coverage of the GaN surface during growth. Using the intensity of the electron beam as a probe,optimum growth conditions of c-GaN were found when a 1 ML Ga coverage is formed at the surface. 1 micrometer thick c-GaN layers had a minimum surface roughness of 2.5 nm when a Ga coverage of 1 ML was established during growth. These samples revealed also a minimum full width at half maximum of the (002)rocking curve.Comment: 3pages with 4 figure

    A Comparison of Approaches for Measuring Cross-Lingual Similarity of Wikipedia Articles

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    Wikipedia has been used as a source of comparable texts for a range of tasks, such as Statistical Machine Translation and CrossLanguage Information Retrieval. Articles written in different languages on the same topic are often connected through inter-language-links. However, the extent to which these articles are similar is highly variable and this may impact on the use of Wikipedia as a comparable resource. In this paper we compare various language-independent methods for measuring cross-lingual similarity: character n-grams, cognateness, word count ratio, and an approach based on outlinks. These approaches are compared against a baseline utilising MT resources. Measures are also compared to human judgements of similarity using a manually created resource containing 700 pairs of Wikipedia articles (in 7 language pairs). Results indicate that a combination of language-independent models (char-ngrams, outlinks and word-count ratio) is highly effective for identifying cross-lingual similarity and performs comparably to language-dependent models (translation and monolingual analysis).The work of the first author was in the framework of the Tacardi research project (TIN2012-38523-C02-00). The work of the fourth author was in the framework of the DIANA-Applications (TIN2012-38603-C02-01) and WIQ-EI IRSES (FP7 Marie Curie No. 269180) research projects.Barrón Cedeño, LA.; Paramita, ML.; Clough, P.; Rosso, P. (2014). A Comparison of Approaches for Measuring Cross-Lingual Similarity of Wikipedia Articles. En Advances in Information Retrieval. Springer Verlag (Germany). 424-429. https://doi.org/10.1007/978-3-319-06028-6_36S424429Adafre, S., de Rijke, M.: Finding Similar Sentences across Multiple Languages in Wikipedia. In: Proc. of the 11th Conf. of the European Chapter of the Association for Computational Linguistics, pp. 62–69 (2006)Dumais, S., Letsche, T., Littman, M., Landauer, T.: Automatic Cross-Language Retrieval Using Latent Semantic Indexing. In: AAAI 1997 Spring Symposium Series: Cross-Language Text and Speech Retrieval, Stanford University, pp. 24–26 (1997)Filatova, E.: Directions for exploiting asymmetries in multilingual Wikipedia. In: Proc. of the Third Intl. Workshop on Cross Lingual Information Access: Addressing the Information Need of Multilingual Societies, Boulder, CO (2009)Levow, G.A., Oard, D., Resnik, P.: Dictionary-Based Techniques for Cross-Language Information Retrieval. Information Processing and Management: Special Issue on Cross-Language Information Retrieval 41(3), 523–547 (2005)Mcnamee, P., Mayfield, J.: Character N-Gram Tokenization for European Language Text Retrieval. Information Retrieval 7(1-2), 73–97 (2004)Mihalcea, R.: Using Wikipedia for Automatic Word Sense Disambiguation. In: Proc. of NAACL 2007. ACL, Rochester (2007)Mohammadi, M., GhasemAghaee, N.: Building Bilingual Parallel Corpora based on Wikipedia. In: Second Intl. Conf. on Computer Engineering and Applications., vol. 2, pp. 264–268 (2010)Munteanu, D., Fraser, A., Marcu, D.: Improved Machine Translation Performace via Parallel Sentence Extraction from Comparable Corpora. In: Proc. of the Human Language Technology and North American Association for Computational Linguistics Conf (HLT/NAACL 2004), Boston, MA (2004)Nguyen, D., Overwijk, A., Hauff, C., Trieschnigg, D.R.B., Hiemstra, D., de Jong, F.: WikiTranslate: Query Translation for Cross-Lingual Information Retrieval Using Only Wikipedia. In: Peters, C., Deselaers, T., Ferro, N., Gonzalo, J., Jones, G.J.F., Kurimo, M., Mandl, T., Peñas, A., Petras, V. (eds.) CLEF 2008. LNCS, vol. 5706, pp. 58–65. Springer, Heidelberg (2009)Paramita, M.L., Clough, P.D., Aker, A., Gaizauskas, R.: Correlation between Similarity Measures for Inter-Language Linked Wikipedia Articles. In: Calzolari, E.A. (ed.) Proc. of the 8th Intl. Language Resources and Evaluation (LREC 2012), pp. 790–797. ELRA, Istanbul (2012)Potthast, M., Stein, B., Anderka, M.: A Wikipedia-Based Multilingual Retrieval Model. In: Macdonald, C., Ounis, I., Plachouras, V., Ruthven, I., White, R.W. (eds.) ECIR 2008. LNCS, vol. 4956, pp. 522–530. Springer, Heidelberg (2008)Simard, M., Foster, G.F., Isabelle, P.: Using Cognates to Align Sentences in Bilingual Corpora. In: Proc. of the Fourth Intl. Conf. on Theoretical and Methodological Issues in Machine Translation (1992)Steinberger, R., Pouliquen, B., Hagman, J.: Cross-lingual Document Similarity Calculation Using the Multilingual Thesaurus EUROVOC. In: Gelbukh, A. (ed.) CICLing 2002. LNCS, vol. 2276, pp. 415–424. Springer, Heidelberg (2002)Toral, A., Muñoz, R.: A proposal to automatically build and maintain gazetteers for Named Entity Recognition using Wikipedia. In: Proc. of the EACL Workshop on New Text 2006. Association for Computational Linguistics, Trento (2006

    Low-dose intra-arterial contrast-enhanced MR aortography in patients based on a theoretically derived injection protocol

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    Multiple intra-arterial contrast agent injections are necessary during MR-guided endovascular interventions. In respect to the approved limits of maximum daily gadolinium dose, a low-dose injection protocol is mandatory. The objective of this study was to derive and apply a low-dose injection protocol for intra-arterial 3D contrast-enhanced MR aortography in patients. Injection rate (Qinj), concentration of injected gadolinium [Gd]inj and aortal blood flow rate (Qblood) were included for the theoretical evaluation of signal intensity (SI) of the arterial lumen. SI simulations were carried out at Qinj=2 versus 4ml/s in the [Gd]inj range between 0-500mM. Qinj and [Gd]inj with SI above the 75% threshold of the maximal SI were regarded as optimal injection parameters. [Gd]inj=50mM and Qinj=4ml/s were considered as optimal and were administered in five patients for 3D MR aortography. All images revealed clear delineation of the abdominal aorta and its major branches. Mean±SD of contrast-to-noise ratios of the abdominal aorta, common iliac and renal artery were 70.2±15.2, 58.6±12.3 and 67.4±12.3. Approximately seven intra-aortal injections would be permissible in patients during MR-guided interventions without exceeding the maximal dose of gadoliniu

    Similarity-aware deep attentive model for clickbait detection

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    © Springer Nature Switzerland AG 2019. Clickbait is a type of web content advertisements designed to entice readers into clicking accompanying links. Usually, such links will lead to articles that are either misleading or non-informative, making the detection of clickbait essential for our daily lives. Automated clickbait detection is a relatively new research topic. Most recent work handles the clickbait detection problem with deep learning approaches to extract features from the meta-data of content. However, little attention has been paid to the relationship between the misleading titles and the target content, which we found to be an important clue for enhancing clickbait detection. In this work, we propose a deep similarity-aware attentive model to capture and represent such similarities with better expressiveness. In particular, we present the ways of either using similarity only or integrating it with other available quality features for the clickbait detection. We evaluate our model on two benchmark datasets, and the experimental results demonstrate the effectiveness of our approach by outperforming a series of competitive state-of-the-arts and baseline methods

    Monte Carlo Procedure for Protein Design

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    A new method for sequence optimization in protein models is presented. The approach, which has inherited its basic philosophy from recent work by Deutsch and Kurosky [Phys. Rev. Lett. 76, 323 (1996)] by maximizing conditional probabilities rather than minimizing energy functions, is based upon a novel and very efficient multisequence Monte Carlo scheme. By construction, the method ensures that the designed sequences represent good folders thermodynamically. A bootstrap procedure for the sequence space search is devised making very large chains feasible. The algorithm is successfully explored on the two-dimensional HP model with chain lengths N=16, 18 and 32.Comment: 7 pages LaTeX, 4 Postscript figures; minor change

    Cross-language high similarity search using a conceptual thesaurus

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    This work addresses the issue of cross-language high similarity and near-duplicates search, where, for the given document, a highly similar one is to be identified from a large cross-language collection of documents. We propose a concept-based similarity model for the problem which is very light in computation and memory. We evaluate the model on three corpora of different nature and two language pairs English-German and English-Spanish using the Eurovoc conceptual thesaurus. Our model is compared with two state-of-the-art models and we find, though the proposed model is very generic, it produces competitive results and is significantly stable and consistent across the corpora.This work was done in the framework of the VLC/CAMPUS Microcluster on Multimodal Interaction in Intelligent Systems and it has been partially funded by the European Commission as part of the WIQ-EI IRSES project (grant no. 269180) within the FP 7 Marie Curie People Framework, and by the Text-Enterprise 2.0 research project (TIN2009-13391-C04-03). The research work of the second author is supported by the CONACyT 192021/302009 grantGupta, P.; Barrón Cedeño, LA.; Rosso, P. (2012). Cross-language high similarity search using a conceptual thesaurus. En Information Access Evaluation. Multilinguality, Multimodality, and Visual Analytics. Springer Verlag (Germany). 7488:67-75. https://doi.org/10.1007/978-3-642-33247-0_8S6775748

    Privacy in crowdsourcing:a systematic review

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    The advent of crowdsourcing has brought with it multiple privacy challenges. For example, essential monitoring activities, while necessary and unavoidable, also potentially compromise contributor privacy. We conducted an extensive literature review of the research related to the privacy aspects of crowdsourcing. Our investigation revealed interesting gender differences and also differences in terms of individual perceptions. We conclude by suggesting a number of future research directions.</p
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