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Digital Twins: Initiatives, Technologies, and Use Cases in the Arab World

Communications of the ACM

Membership in ACM includes a subscription to Communications of the ACM (CACM), the computing industry's most trusted source for staying connected to the world of advanced computing. Digital twins (DTs) are virtual replicas of components, assets, systems, or processes, linked to their real-world counterparts, continuously updating their states and simulating their behavior in real-time, as illustrated in Figure 1 . They are adopted for monitoring, predicting, and optimizing the performance of diverse systems, bridging the gap between design, testing and deployment. Significant efforts are being devoted across Arab R&D institutions to export technology tackling challenges that are not only pertinent to the region, but also of global importance, e.g., energy, sustainability, disaster management, healthcare, and urbanization, among many others. For instance, Khalifa University, UAE, is pioneering research into optical wireless communication using DTs.


A Proof of Theorem 2

Neural Information Processing Systems

We prove the universal approximation theorem by showing the equivalence of TFN and our model. Complex spherical harmonics are related to Clebsch-Gordan coefficients via [51, 3.7.72] We can therefore adapt Eq. (2) by substituting C To see this, we look at the result's real component null [ H To prove this theorem we first introduce a proposition by Villar et al. [57]. GemNet's variance varies strongly between layers and increases significantly after each block without scaling factors (top). We use 4 stacked interaction blocks and an embedding size of 128 throughout the model.









FWI: Large-scale Multi-structural Benchmark Datasets for Full Waveform Inversion Chengyuan Deng

Neural Information Processing Systems

Full waveform inversion (FWI) is widely used in geophysics to reconstruct high-resolution velocity maps from seismic data. The recent success of data-driven FWI methods results in a rapidly increasing demand for open datasets to serve the geophysics community.