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Representation of Concepts in AI: Towards a Teleological Explanation.

, and . JOWO, volume 2518 of CEUR Workshop Proceedings, CEUR-WS.org, (2019)

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Ages of massive galaxies at $0.5 < z < 2.0$ from 3D-HST rest-frame optical spectroscopy, , , , , , , , , and 3 other author(s). (2016)cite arxiv:1603.02689Comment: 13 pages, 15 figures, accepted for publication in ApJ.Ontological Analysis and Redesign of Security Modeling in ArchiMate., , , , , and . PoEM, volume 456 of Lecture Notes in Business Information Processing, page 82-98. Springer, (2022)Ontology-Driven Cross-Domain Transfer Learning., , , and . FOIS, volume 330 of Frontiers in Artificial Intelligence and Applications, page 249-263. IOS Press, (2020)Confirmation of Small Dynamical and Stellar Masses for Extreme Emission Line Galaxies at z~2, , , , , , , , , and 14 other author(s). (2013)cite arxiv:1310.6358Comment: Accepted for publication in ApJL, 5 pages, 1 table, 4 figures.Direct measurement of dust attenuation in z~1.5 star-forming galaxies from 3D-HST: Implications for dust geometry and star formation rates, , , , , , , , , and 5 other author(s). (2013)cite arxiv:1310.4177Comment: Submitted for publication in the Astrophysical Journal.Where stars form: inside-out growth and coherent star formation from HST Halpha maps of 2676 galaxies across the main sequence at z~1, , , , , , , , , and 10 other author(s). (2015)cite arxiv:1507.03999Comment: Submitted to ApJ. Main results: Fig. 6 shows the scale lengths of ionized gas vs. stellar disks. Fig. 9 shows where Halpha in galaxies is enhanced above and suppressed below the star-forming main sequence. Data points for Halpha profiles are available upon request.On Knowledge Diversity., and . JOWO, volume 2518 of CEUR Workshop Proceedings, CEUR-WS.org, (2019)An Ontology-Driven Approach for Process-Aware Risk Propagation., , , , , and . SAC, page 1742-1745. ACM, (2023)How FAIR are Security Core Ontologies? A Systematic Mapping Study., , , and . RCIS, volume 415 of Lecture Notes in Business Information Processing, page 107-123. Springer, (2021)Boosting D3FEND: Ontological Analysis and Recommendations., , , , , , , and . FOIS, volume 377 of Frontiers in Artificial Intelligence and Applications, page 334-348. IOS Press, (2023)