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CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures
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33%; open Qiu, L. & Riesbeck, C. K. (2004) Find in CUMINCAD Incremental Authoring of Computer-based Interactive Learning Environments for Problem-based Learning , IEEE Intern’l Conf. on Advanced Learning Technologies (ICALT). Finland, IEEE Press. 171 - 175
33%; open Qomi, M. J. A., Brochard, L., Honorio, T., Maruyama, I., & Vandamme, M. (2021) Find in CUMINCAD Advances in Atomistic Modeling and Understanding of Drying Shrinkage in Cementitious Materials , Cement and Concrete Research, 148, 16536, Available at: https://doi.org/1.116/j.cemconres.221.16536.
33%; open Quarantelli, E. L. (1982) Find in CUMINCAD General and particular observations on sheltering and housing in American disasters , Disasters, 6, pp. 277-281
33%; open Quarantelli, E. L. (1997) Find in CUMINCAD Computer based information/communication revolution: ten problematical issues and questions they raise for disaster planning and managing , University of Delaware: Disaster Research Center, Newark, DE
33%; open Quero, L.C., Bartolomé, J.I., and Cho, J. (2021) Find in CUMINCAD Accessible visual artworks for blind and visually impaired people: comparing a multimodal approach with tactile graphics , Electronics 10, 297
33%; open Qvortrup, L. (2002) Find in CUMINCAD Cyberspace as Representation of Space Experience: In Defence of a Phenomenological Approach , L. Qvortrup (ed) Virtual Space: Spatiality in Virtually Inhabited 3d Worlds, Springer-Verlag, London, pp. 5-24
33%; open R. Auras, L.-T. Lim, S. E. M. Selke, and H. Tsuji, eds (2010) Find in CUMINCAD Poly(Lactic Acid): Synthesis, Structures, Properties, Processing, and Applications , Hoboken, NJ: John Wiley & Sons
33%; open R. Jin, Zhong, B., Ma, L., Hashemi, A. & Ding, L. (2019) Find in CUMINCAD Integrating bim with building performance analysis in project life-cycle , Automation in Construction, 106, 102861. https://doi.org/10.1016/j.autcon.2019.102861
33%; open R. L. Johns (2014) Find in CUMINCAD Augmented Materiality Modelling with Material Indeterminacy , Fabricate, 216–223
33%; open R. Lorenzo, L. Mimendi, H. Li, and D. Yang (2020) Find in CUMINCAD Bimodulus bending model for bamboo poles , Construction and Building Materials 262 (Nov): 120876
33%; open R. Naboni, L. Breseghello, and A. Kunic (2019) Find in CUMINCAD Multi-Scale Design and Fabrication of the Trabeculae Pavilion , Additive Manufacturing 27(May): 305–317
33%; open R. Rajkumar, I. Lee, L. Sha, and J. Stankovic (2010) Find in CUMINCAD Cyber-physical systems: The next computing revolution , 47th ACM/IEEE Des. Autom. Conferfence, 731–736
33%; open R.D.Kalnins, L.Markosian, B.J.Meier, M.A,Kowalski, J.C.Lee, P.L.Davidson, M.Webb, J.F.Hughes, A.Finkelstein, WYSIWYG NPR (2002) Find in CUMINCAD Drawing strokes directly on 3d models , SIGGRAPH2002, pp.755-762
33%; open Rabiner, L.R. and Juang B.H. (1986) Find in CUMINCAD An introduction to Hidden Markov Models , IEEE ASSP Mag., pp 4-16
33%; open Raccoon, L.B.S. (1995) Find in CUMINCAD The Chaos Model and the Chaos Life Cycle , ACM SIGSOFT, Software Engineering Notes, 20 (1), 55- 66
33%; open Raccoon, L.B.S. (1995) Find in CUMINCAD The Chaos Model and the Chaos Life Cycle , ACM Sigsoft Software Engineering Notes, January 1995.Vol.20, n.1, 56–57
33%; open Radford A, Metz L and Chintala S (2015) Find in CUMINCAD Unsupervised representation learning with deep convolutional generative adversarial networks, , http://arxiv.org/pdf/1511.06434v2 (2015).
33%; open Radford A, Metz L and Chintala S (2016) Find in CUMINCAD Unsupervised representation learning with deep convolutional generative adversarial networks, 2016 , ArXiv:1511.06434 [Cs] http://arxiv.org/abs/1511.06434
33%; open Radford A. and Stevens, G. (1988) Find in CUMINCAD Role Play in Education: A Case Study from Architectural Computing , Journal of Architecture Education, 42(l): 18-23
33%; open Radford, A, Metz, L and Chintala, S (2015) Find in CUMINCAD Unsupervised representation learning with deep convolutional generative adversarial networks , arXiv preprint arXiv:1511.06434, 1, pp. 1-5

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