Macedo, H. D., Bayard Rasmussen, M., Thule, C. & Larsen, P. G. (2020).
Migrating the INTO-CPS Application to the Cloud. In 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 (Eds.),
Formal Methods: FM 2019 International Workshops (pp. 254-271). Springer.
https://doi.org/10.1007/978-3-030-54997-8_17
Yuksel, O.
, Sandberg, M., Hattel, J. H., Akkerman, R. & Baran, I. (2021).
Mesoscale Process Modeling of a Thick Pultruded Composite with Variability in Fiber Volume Fraction.
Materials,
14(13), Article 3763.
https://doi.org/10.3390/ma14133763
Nuka, G.
& Woodcock, J. (2006).
Mechanising a Unifying Theory. In S. Dunne & B. Stoddart (Eds.),
Unifying Theories of Programming: First International Symposium, UTP 2006, Walworth Castle, County Durham, UK, February 5-7, 2006, Revised Selected Papers (pp. 217-235). Springer.
https://doi.org/10.1007/11768173_13
Yuksel, O.
, Sandberg, M., Baran, I., Ersoy, N., Hattel, J. H. & Akkerman, R. (2021).
Material characterization of a pultrusion specific and highly reactive polyurethane resin system: Elastic modulus, rheology, and reaction kinetics.
Composites Part B: Engineering,
207, Article 108543.
https://doi.org/10.1016/j.compositesb.2020.108543
Bajovic, D.
, Bakhtiarnia, A., Bravos, G., Brutti, A., Burkhardt, F., Cauchi, D., Chazapis, A., Cianco, C., Dall'Asen, N., Delic, V., Dimou, C., Djokic, D., Escobar-Molero, A.
, Esterle, L., Eyben, F., Farella, E., Festi, T., Geromitsos, A., Giakoumakis, G. ... Zammit, J. (2021).
MARVEL: Multimodal Extreme Scale Data Analytics for Smart Cities Environments. In
2021 International Balkan Conference on Communications and Networking, BalkanCom 2021 (pp. 143-147). IEEE.
https://doi.org/10.1109/BalkanCom53780.2021.9593258
Thule, C., Lausdahl, K. G., Gomes, C., Meisl, G.
& Larsen, P. G. (2019).
Maestro: The INTO-CPS co-simulation framework.
Simulation Modelling Practice and Theory,
92, 45-61.
https://doi.org/10.1016/j.simpat.2018.12.005
Esterle, L., Montagna, S., Pianini, D., Aguzzi, G., Bellman, K. L., Ciatto, G., Contoli, C., Donati, M., Mariani, S., Rahmani, A., Savaglio, C., Storti, E., TaheriNejad, N., van der Sluis, O. & Wang, Z. (2024).
MADTECC 2024: 1st Workshop on Medical Applications with Digital Twins and Edge-cloud Continuum - Welcome and Committees. In
2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) (pp. 30-31). IEEE.
https://doi.org/10.1109/PerComWorkshops59983.2024.10502899
Lewis, P. R.
, Esterle, L., Chandra, A., Rinner, B. & Yao, X. (2013).
Learning to be different: Heterogeneity and efficiency in distributed smart camera networks.
International Conference on Self-Adaptive and Self-Organizing Systems, SASO, 209-218.
https://doi.org/10.1109/SASO.2013.20
Bennedsen, J., Keiding, T. B. & Godsk, M. (2020).
Learning design and the tension between strategy and didactics. In J. Malmqvist, J. Bennedsen, K. Edström, N. Kuptasthien, A. Sripakagorn, J. Roslöf, I. Saemundsdottir & M. Siiskonen (Eds.),
The 16th International CDIO Conference: Proceedings – Full Papers (Vol. 2, pp. 285-295). Chalmers tekniska högskola.
https://research.chalmers.se/publication/519263/file/519263_Fulltext.pdf
Beevi, F. H. A., Pedersen, C. F., Wagner, S. R. & Hallerstede, S. (2014).
Lateral Fall Detection via Events in Linear Prediction Residual of Acceleration. In C. Ramos, P. Novais, C. Ehrwein Nihan & J. M. Corchado Rodriguez (Eds.),
Ambient Intelligence - Software and Applications: 5th International Symposium on Ambient Intelligence (Vol. 291, pp. 201-208). Springer.
https://doi.org/10.1007/978-3-319-07596-9_22
Amiri, M., Dehghani, M., Khayatian, A., Mohammadi, M.
, Vafamand, N. & Boudjadar, J. (2021).
Investigation of Wind Energy Impact on Power Systems Stability Using Lyapunov Exponents. In H. Selvaraj, G. Chmaj & D. Zydek (Eds.),
Proceedings of the 27th International Conference on Systems Engineering, ICSEng 2020 (pp. 12-22). Springer.
https://doi.org/10.1007/978-3-030-65796-3_2
Guimarães, G., Costa, I., Perkusich, M.
, Mendes, E., Santos, D., Almeida, H. & Perkusich, A. (2024).
Investigating the relationship between personalities and agile team climate: A replicated study.
Information and Software Technology,
169, Article 107407.
https://doi.org/10.1016/j.infsof.2024.107407
Feng, H., Gomes, C., Thule, C., Lausdahl, K., Iosifidis, A. & Larsen, P. G. (2021).
Introduction to Digital Twin Engineering. In C. R. Martin, M. J. Blas & A. I. Psijas (Eds.),
2021 Annual Modeling and Simulation Conference (ANNSIM) (pp. 1-12). IEEE.
https://doi.org/10.23919/ANNSIM52504.2021.9552135
Talasila, P., Sanjari, A., Villadsen, K., Thule, C., Larsen, P. G. & Macedo, H. D. (2021).
Introducing Regression Tests and Upgrades to the INTO-CPS Application. In L. Cleophas & M. Massink (Eds.),
Software Engineering and Formal Methods. SEFM 2020 Collocated Workshops - ASYDE, CIFMA, and CoSim-CPS, 2020, Revised Selected Papers: ASYDE, CIFMA, and CoSim-CPS, Amsterdam, The Netherlands, September 14–15, 2020, Revised Selected Papers (pp. 311-317). Springer.
https://doi.org/10.1007/978-3-030-67220-1_23
Bandur, V., Larsen, P. G., Lausdahl, K., Thule, C., Gamble, C., Payne, R., Pop, A., Brosse, E., Brauer, J., Lapschies, F., Groothuis, M., Bokhove, T., Kleijn, C. & Couto, L. D. (2017).
INTO-CPS tool chain user manual. Aarhus University.
https://into-cps.github.io/download/
Glässer, U.
, Hallerstede, S., Leuschel, M. & Riccobene, E. (2014).
Integration of Tools for Rigorous Software Construction and Analysis. In U. Glässer, S. Hallerstede, M. Leuschel & E. Riccobene (Eds.),
Integration of Tools for Rigorous Software Construction and Analysis (Dagstuhl Seminar 13372) (Vol. Dagstuhl Reports, Volume 3, Issue 9). Dagstuhl Publishing.
https://doi.org/10.4230/DagRep.3.9.74
Feng, H., Gomes, C., Gil Arboleda, S., Mikkelsen, P. H., Tola, D., Larsen, P. G. & Sandberg, M. (2022).
Integration Of The Mape-K Loop In Digital Twins. In C. R. Martin, N. Emami, M. J. Blas & R. Rezaee (Eds.),
Proceedings of the 2022 Annual Modeling and Simulation Conference, ANNSIM (pp. 102-113). IEEE.
https://doi.org/10.23919/ANNSIM55834.2022.9859489