Publikationer

Søg publikationer fra Institut for Datalogi

Liste over publikationer af videnskabelige medarbejdere fra Institut for Datalogi, Aarhus Universitet.

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Nielsen, J. B. (2015). Tamper and leakage resilient von Neumann architectures from continuous non-malleable codes. I S. Wolf & A. Lehmann (red.), 8th International Conference on Information Theoretic Security, ICITS 2015 (Bind 9063, s. XI-XII). Springer.

Nielsen, M., Brewer, R. S. & Grønbæk, K. (2016). Supporting interactive visual analytics of energy behavior in buildings through affine visualizations. I Proceedings of the 28th Australian Computer-Human Interaction Conference, OzCHI 2016 (s. 238-247). Association for Computing Machinery. https://doi.org/10.1145/3010915.3010950

Nielsen, M., Elmqvist, N. & Grønbæk, K. (2016). Scribble query: fluid touch brushing for multivariate data visualization. I Proceedings of the 28th Australian Computer-Human Interaction Conference, OzCHI 2016 (s. 381-390). Association for Computing Machinery. https://doi.org/10.1145/3010915.3010951

Nielsen, J. B. & Orlandi, C. (2016). Cross and Clean: Amortized Garbled Circuits with Constant Overhead. I M. Hirt & A. Smith (red.), Theory of Cryptography - 14th International Conference, TCC 2016-B, Proceedings (Bind 9985, s. 582-603). Springer VS. https://doi.org/10.1007/978-3-662-53641-4_22

Nielsen, J. B. & Ranellucci, S. (2016). Reactive garbling: Foundation, instantiation, application. I J. H. Cheon & T. Takagi (red.), Advances in Cryptology - ASIACRYPT 2016 - 22nd International Conference on the Theory and Application of Cryptology and Information Security, Proceedings (Bind 10032, s. 1022-1052). Springer VS. https://doi.org/10.1007/978-3-662-53890-6_34

Nielsen, J. B. & Ranellucci, S. (2016). On the Computational Overhead of MPC with Dishonest Majority. http://eprint.iacr.org/2016/643

Nielsen, J. B., Schneider, T. & Trifiletti, R. (2017). Constant Round Maliciously Secure 2PC with Function-independent Preprocessing using LEGO. I NDSS ’17 (s. 1-15). Internet Society. https://doi.org/10.14722/ndss.2017.23075

Nielsen, K., Sillasen, M. K. & Daugbjerg, P. S. (2017). Engineering - svaret på naturfagenes udfordringer? MONA: Matematik og Naturfagsdidaktik, 2017-2, 64. https://tidsskrift.dk/mona/article/view/36656

Nielsen, B. L. & Nielsen, K. (2017). Kompetenceudvikling for undervisere/pædagogisk personale. I J. A. Nielsen (red.), Litteraturstudium til arbejdet med en national naturvidenskabsstrategi (s. 50-72). Institut for Naturfagenes Didaktik, Københavns Universitet. https://astra.dk/sites/default/files/Naturvidenskabsstrategi_Litteraturstudium_Rapport.pdf

Nielsen, K. & Horst, S. (2017). Sammen om naturvidenskabsstrategien. MONA: Matematik og Naturfagsdidaktik, 2017(03), 61-71. https://tidsskrift.dk/mona/article/download/96861/145618

Nielsen, K., Daugbjerg, P. S. & Sillasen, M. (2017). Engineering - en uddybende kommentar til en kommentar fra Kolmos og Grunwald. MONA - Matematik- og Naturfagsdidaktik, 2017(03), 95-97.

Nielsen, J. B. & Ranellucci, S. (2017). On the computational overhead of MPC with dishonest majority. I S. Fehr (red.), Public-Key Cryptography – PKC 2017 - 20th IACR International Conference on Practice and Theory in Public-Key Cryptography, Proceedings (Bind 10175, s. 369-395). Springer VS. https://doi.org/10.1007/978-3-662-54388-7_13

Nielsen, K. (2019). Engineering og teknologiforståelse. I Engineering (s. 84-99). VIA University College.

Nielsen, B. B., Hassanshahi, B. & Gauthier, F. (2019). Nodest: Feedback-driven static analysis of Node.js applications. I S. Apel, M. Dumas, A. Russo & D. Pfahl (red.), ESEC/FSE 2019 - Proceedings of the 2019 27th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering (s. 455-465). Association for Computing Machinery. https://doi.org/10.1145/3338906.3338933

Nielsen, J. B. & Spitters, B. (2019). Smart Contract Interactions in Coq. (0 udg.) ArXiv.

Nielsen, L. H., Andersen, M. H., Petersen, M. G., Bouvin, N. O. & Hjorth, H. A. (2020). A Collaborative Cross-Device Microworld for Physics Simulation Experiments in High-School. I B. Tangney, J. R. Byrne & C. Girvan (red.), Proceedings of the 2020 Constructionism Conference (s. 119-128). http://www.constructionismconf.org/wp-content/uploads/2020/05/C2020-Proceedings.pdf

Nielsen, J. B. & Spitters, B. (2020). Smart contract interactions in coq. I E. Sekerinski, N. Moreira, J. N. Oliveira, D. Ratiu, R. Guidotti, M. Farrell, M. Luckcuck, D. Marmsoler, J. Campos, T. Astarte, L. Gonnord, A. Cerone, L. Couto, B. Dongol, M. Kutrib, P. Monteiro & D. Delmas (red.), Formal Methods- FM 2019 International Workshops - Revised Selected Papers (s. 380-391). Springer. https://doi.org/10.1007/978-3-030-54994-7_29

Nielsen, K. & Sillasen, M. K. (2019). En tiltrængt røst: Kommentar til Jette Reuss Schmidt "Hvem definerer STEM i skolefag og i skoleforskningen?", MONA, 2019(2). MONA - Matematik- og Naturfagsdidaktik, (3), 102-108. https://tidsskrift.dk/mona/article/view/115588

Nielsen, J. B. & Simkin, M. (2020). Lower bounds for leakage-resilient secret sharing. I A. Canteaut & Y. Ishai (red.), Advances in Cryptology – EUROCRYPT 2020 - 39th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Proceedings (s. 556-577). Springer. https://doi.org/10.1007/978-3-030-45721-1_20

Nielsen, B. B. & Møller, A. (2020). Value Partitioning: A Lightweight Approach to Relational Static Analysis for JavaScript. I 34th European Conference on Object-Oriented Programming, ECOOP 2020 Artikel 16 Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.ECOOP.2020.16

Nielsen, B. B., Torp, M. T. & Møller, A. (2020). Detecting Locations in JavaScript Programs Affected by Breaking Library Changes. Proceedings of the ACM on Programming Languages , 4(OOPSLA), Artikel 187. https://doi.org/10.1145/3428255

Nielsen, B. B., Torp, M. T. & Møller, A. (2021). Modular call graph construction for security scanning of Node.js applications. I C. Cadar & X. Zhang (red.), ISSTA 2021 - Proceedings of the 30th ACM SIGSOFT International Symposium on Software Testing and Analysis (s. 29-41). Association for Computing Machinery. https://doi.org/10.1145/3460319.3464836

Nielsen, B. B., Torp, M. T. & Møller, A. (2021). Semantic Patches for Adaptation of JavaScript Programs to Evolving Libraries. I Proceedings - 2021 IEEE/ACM 43rd International Conference on Software Engineering, ICSE 2021 (s. 74-85). IEEE. https://doi.org/10.1109/ICSE43902.2021.00020

Nielsen, S. D.-H., Liang, N., Rathish, H., Kim, B. J., Lueangsakulthai, J., Koh, J., Qu, Y., Schulz, H.-J. & Dallas, D. C. (2024). Bioactive milk peptides: an updated comprehensive overview and database. Critical Reviews in Food Science and Nutrition, 64(31), 11510-11529. https://doi.org/10.1080/10408398.2023.2240396

Nielsen, E. H., Annenkov, D. & Spitters, B. (2023). Formalising Decentralised Exchanges in Coq. I R. Krebbers, D. Traytel, B. Pientka & S. Zdancewic (red.), CPP '23: 12th ACM SIGPLAN International Conference on Certified Programs and Proofs (s. 290-302). Association for Computing Machinery. https://doi.org/10.1145/3573105.3575685

Nielsen, J. A. S. (2015). Implicit Data Structures, Sorting, and Text Indexing. Department of Computer Science, Aarhus University.

Nielsen, M. (2019). Correlated randomness in cryptographic protocols. Århus Universitet.

Nielsen, B. B. (2021). Static Analysis for Node.js. Århus Universitet.

Nielsen, S. (2018). Inferring gene flow between populations using statistical methods. Århus Universitet.

Nielsen, M. (2016). Interactive Visual Analytics of Big Data - a Web-Based Approach. Department of Computer Science, Aarhus University.

Newburger, E. & Elmqvist, N. (2024). Visualization According to Statisticians: An Interview Study on the Role of Visualization for Inferential Statistics. IEEE Transactions on Visualization and Computer Graphics, 30(1), 230-239. https://doi.org/10.1109/TVCG.2023.3326521

Neumann, L., Guimaraes, A., Aranha, D. F. & Borin, E. (2024). Homomorphic WiSARDs: Efficient Weightless Neural Network training over encrypted data. Abstract fra 4th Workshop on Artificial Intelligence and Cryptography, Zurich, Schweiz. https://arxiv.org/abs/2403.20190

Neumann, L., Guimaraes, A., Aranha, D. F. & Borin, E. (2025). Homomorphic WiSARDs: Efficient Weightless Neural Network training over encrypted data. I Proceedings of ACNS 2025 https://doi.org/10.1007/978-3-031-95767-3_12

Nelson, B., Pagnin, E. & Askarov, A. (2024). Metadata Privacy Beyond Tunneling for Instant Messaging. I Proceedings - 9th IEEE European Symposium on Security and Privacy, EuroS&P 2024 (s. 697-723). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EuroSP60621.2024.00044

Neerbek, J., Assent, I. & Dolog, P. (2017). TABOO: Detecting unstructured sensitive information using recursive neural networks. I Proceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017 (s. 1399-1400). Artikel 7930091 IEEE Computer Society Press. https://doi.org/10.1109/ICDE.2017.195

Neerbek, J., Dolog, P. & Assent, I. (2019). Selective Training: A Strategy for Fast Backpropagation on Sentence Embeddings. I Q. Yang, M.-L. Zhang, Z. Gong, S.-J. Huang & Z.-H. Zhou (red.), Advances in Knowledge Discovery and Data Mining - 23rd Pacific-Asia Conference, PAKDD 2019, Proceedings: PAKDD '19 (s. 40-53). Springer. https://doi.org/10.1007/978-3-030-16142-2_4

Neerbek, J., Assent, I. & Dolog, P. (2018). Detecting Complex Sensitive Information via Phrase Structure in Recursive Neural Networks. I D. Phung, V. S. Tseng, G. I. Webb, B. Ho, M. Ganji & L. Rashidi (red.), Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Proceedings: PAKDD '18 (Bind 10939, s. 373-385). Springer VS. https://doi.org/10.1007/978-3-319-93040-4_30

Neerbek, J., Eskildsen, M., Dolog, P. & Assent, I. (2020). A real-world data resource of complex sensitive sentences based on documents from the Monsanto trial. I N. Calzolari, F. Bechet, P. Blache, K. Choukri, C. Cieri, T. Declerck, S. Goggi, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk & S. Piperidis (red.), LREC 2020 - 12th International Conference on Language Resources and Evaluation, Conference Proceedings (s. 1258-1267). European Language Resources Association.

Neerbek, J. (2020). Sensitive Information Detection: Recursive Neural Networks for Encoding Context. Århus Universitet.

Neele, T. & Pol, J. V. D. (2024). Operations on Fixpoint Equation Systems. Logical Methods in Computer Science, 20(3), 5:1-5:32. https://doi.org/10.46298/LMCS-20(3:5)2024

Nayara Ortiz, J., Ricardo de Araujo, R., Aranha, D. F., Rodrigues Costa, S. I. & Dahab, R. (2021). The Ring-LWE Problem in Lattice-based Cryptography: The Case of Twisted Embeddings. Entropy, 23(9), Artikel 1108. https://doi.org/10.3390/e23091108

Nasir, M. A. U., Aslay, C., de Francisi Morales, G. & Riondato, M. (2021). TipTap: Approximate Mining of Frequent k-Subgraph Patterns in Evolving Graphs. ACM Transactions on Knowledge Discovery from Data, 15(3), 1-35. Artikel 48. https://doi.org/10.1145/3442590

Musaeus, L. H., Nielsen, K., Damsgaard-Madsen, M. & Hansen, J. Ø. (2020). Computational thinking i gymnasiefag: en modelbaseret didaktik. Århus Universitet. https://cs.au.dk/fileadmin/www.cct.au.dk/cctd.au.dk/PDFs/CT-didaktik2020.pdf

Musaeus, L. H., Petersen, M. G., Klokmose, C. N. & Iversen, O. S. (2022). CoTinker - A Toolkit for Supporting Computational Thinking and Collaboration in High School Education. I SIGCSE 2022: Proceedings of the 53rd ACM Technical Symposium on Computer Science Education (Bind 2, s. 1025). Association for Computing Machinery. https://doi.org/10.1145/3478432.3499234

Musaeus, L. H., Sørensen, M.-L. S. K., Palfi, B. S., Iversen, O. S., Klokmose, C. N. & Petersen, M. G. (2022). CoTinker: Designing a Cross-device Collaboration Tool to Support Computational Thinking in Remote Group Work in High School Biology. I Participative Computing for Sustainable Futures : Proceedings of the 12th Nordic Conference on Human-Computer Interaction (NordiCHI’22) Artikel 49 Association for Computing Machinery. https://doi.org/10.1145/3546155.3546709

Musaeus, L. H., Van Mechelen, M., Caspersen, M. E. & Iversen, O. S. (2022). Empowerment through computational thinking: A literature survey. Acta Didactica Norden, 16(4), Artikel 1. https://doi.org/10.5617/adno.9152

Musaeus, L. H., Hansen, J. Ø. & Nielsen, K. (2023). Computational thinking i matematik, naturfag og samfundsfag: hvorfor, hvad og hvordan? . MONA - Matematik- og Naturfagsdidaktik, 2023(1), 45-71.

Musaeus, L. H., Petersen, M. G. & Klokmose, C. N. (2024). Bringing Teachers and Researchers together through Participatory Design and Cooperative Prototyping in Computing Education. I SIGCSE 2024 - Proceedings of the 55th ACM Technical Symposium on Computer Science Education (Bind 1, s. 902-908). Association for Computing Machinery. https://doi.org/10.1145/3626252.3630796

Musaeus, L. H. & Musaeus, P. (2024). Computational Thinking and Modeling: A Quasi-Experimental Study of Learning Transfer. Education Sciences, 14(9), Artikel 980. https://doi.org/10.3390/educsci14090980

Musaeus, L. H. (2025). Fostering Students’ Comprehension of Generative AI in Informatics Education in High School. 1. Poster-session præsenteret på ISLS annual meeting, Helsinki, Finland. https://sites.google.com/view/isls2025nms#h.9j0gw0lhuegi

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